The goal of simulateDCE is to make it easy to simulate choice experiment
datasets using designs from NGENE, idefix or spdesign. You have to
store the design file(s) in a subfolder and need to specify certain
parameters and the utility functions for the data generating process.
The package is useful for:
-
Test different designs in terms of statistical power, efficiency and unbiasedness
-
To test the effects of deviations from RUM, e.g. heuristics, on model performance for different designs.
-
In teaching, using simulated data is useful, if you want to know the data generating process. It helps to demonstrate Maximum likelihood and choice models, knowing exactly what you should expect.
-
You can use simulation in pre-registration to justify your sample size and design choice.
-
Before data collection, you can use simulated data to estimate the models you plan to use in the actual analysis. You can thus make sure, you can estimate all effects for given sample sizes.
You can install simulateDCE from github. You need to install the
devtools package first. The current version is alpha and there is no
version on cran:
install.packages("devtools")
devtools::install_git('https://github.com/sagebiej/simulateDCE', ref = "main")For the latest development version use this:
install.packages("devtools")
devtools::install_git('https://github.com/sagebiej/simulateDCE', ref = "devel")This is a basic example for a simulation:
rm(list=ls())
library(simulateDCE)
library(rlang)
library(formula.tools)
#>
#> Attaching package: 'formula.tools'
#> The following object is masked from 'package:rlang':
#>
#> env
designpath<- system.file("extdata","SE_DRIVE" ,package = "simulateDCE")
resps =120 # number of respondents
nosim= 400 # number of simulations to run (about 500 is minimum)
# bcoeff <- list(
# bpreis = -0.036,
# blade = -0.034,
# bwarte = -0.049)
decisiongroups=c(0,0.7,1)
# wrong parameters
# place b coefficients into an r list:
bcoeff = list(
bpreis = -0.01,
blade = -0.07,
bwarte = 0.02)
manipulations = list(alt1.x2= expr(alt1.x2/10),
alt1.x3= expr(alt1.x3/10),
alt2.x2= expr(alt2.x2/10),
alt2.x3= expr(alt2.x3/10)
)
#place your utility functions here
ul<-list( u1 =
list(
v1 =V.1~ bpreis * alt1.x1 + blade*alt1.x2 + bwarte*alt1.x3 ,
v2 =V.2~ bpreis * alt2.x1 + blade*alt2.x2 + bwarte*alt2.x3
)
,
u2 = list( v1 =V.1~ bpreis * alt1.x1 ,
v2 =V.2~ bpreis * alt2.x1)
)
destype="ngene"
sedrive <- sim_all(nosim = nosim, resps=resps, destype = destype,
designpath = designpath, u=ul, bcoeff = bcoeff, decisiongroups = decisiongroups)
#> 'simple' is deprecated and will be removed in the future. Use 'exact' instead.
#> bcoeff_lookup already exists; skipping modification.
#> Utility function used in simulation, ie the true utility:
#>
#> $u1
#> $u1$v1
#> V.1 ~ bpreis * alt1.x1 + blade * alt1.x2 + bwarte * alt1.x3
#> <environment: 0x5cc5fbecc2e0>
#>
#> $u1$v2
#> V.2 ~ bpreis * alt2.x1 + blade * alt2.x2 + bwarte * alt2.x3
#> <environment: 0x5cc5fbf0ffd8>
#>
#>
#> $u2
#> $u2$v1
#> V.1 ~ bpreis * alt1.x1
#> <environment: 0x5cc5fbf32890>
#>
#> $u2$v2
#> V.2 ~ bpreis * alt2.x1
#> <environment: 0x5cc5fbf54428>
#> 'destype' is deprecated. Please use 'designtype' instead.
#> New names:
#> • `Choice situation` -> `Choice.situation`
#> • `` -> `...10`
#>
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5346621 0.7318508 -1.0846621 -11.868149 1
#> 2 1 -0.95 -2.35 0.5773936 -0.7811993 -0.3726064 -3.131199 1
#> 3 1 -6.20 -2.30 1.3382771 0.1158697 -4.8617229 -2.184130 2
#> 4 1 -13.90 -2.55 1.0026198 0.9662150 -12.8973802 -1.583785 2
#> 5 1 -14.40 -5.80 0.4685361 -0.4860094 -13.9314639 -6.286009 2
#> 6 1 -3.60 -1.70 2.5243715 0.6438044 -1.0756285 -1.056196 2
#>
#>
#> Transformed utility function (type: simple ):
#> [1] "U_1 = @bpreis * $alt1_x1 + @blade * $alt1_x2 + @bwarte * $alt1_x3 ;U_2 = @bpreis * $alt2_x1 + @blade * $alt2_x2 + @bwarte * $alt2_x3 ;"
#> This is Run number 1
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0480412 1.0658687 1.4980412 -11.5341313 1
#> 2 1 -0.95 -2.35 1.6458423 3.0029775 0.6958423 0.6529775 1
#> 3 1 -6.20 -2.30 0.8064037 1.7156233 -5.3935963 -0.5843767 2
#> 4 1 -13.90 -2.55 -0.9656518 0.7281514 -14.8656518 -1.8218486 2
#> 5 1 -14.40 -5.80 -0.8679570 3.8650136 -15.2679570 -1.9349864 2
#> 6 1 -3.60 -1.70 0.7468481 1.9040151 -2.8531519 0.2040151 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -38650 7050
#> initial value 998.131940
#> iter 2 value 814.051264
#> iter 3 value 803.513852
#> iter 4 value 803.277976
#> iter 5 value 766.362532
#> iter 6 value 757.804164
#> iter 7 value 756.391651
#> iter 8 value 756.360304
#> iter 9 value 756.360241
#> iter 10 value 756.360224
#> iter 10 value 756.360214
#> iter 10 value 756.360206
#> final value 756.360206
#> converged
#> This is Run number 2
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.95903510 1.7469021 -1.5090351 -10.8530979 1
#> 2 1 -0.95 -2.35 0.48567293 1.3550837 -0.4643271 -0.9949163 1
#> 3 1 -6.20 -2.30 -0.07062326 -0.3819651 -6.2706233 -2.6819651 2
#> 4 1 -13.90 -2.55 -0.27359542 1.7458482 -14.1735954 -0.8041518 2
#> 5 1 -14.40 -5.80 0.62747982 1.1230906 -13.7725202 -4.6769094 2
#> 6 1 -3.60 -1.70 5.51924738 0.5975311 1.9192474 -1.1024689 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7320 -40200 5325
#> initial value 998.131940
#> iter 2 value 798.413557
#> iter 3 value 790.367792
#> iter 4 value 788.829313
#> iter 5 value 756.684783
#> iter 6 value 747.942494
#> iter 7 value 746.186623
#> iter 8 value 746.134114
#> iter 9 value 746.133922
#> iter 10 value 746.133904
#> iter 10 value 746.133904
#> iter 10 value 746.133894
#> final value 746.133894
#> converged
#> This is Run number 3
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3494364 -1.2638437 -0.8994364 -13.8638437 1
#> 2 1 -0.95 -2.35 -1.0591545 -0.3654889 -2.0091545 -2.7154889 1
#> 3 1 -6.20 -2.30 -0.6391097 -1.0715919 -6.8391097 -3.3715919 2
#> 4 1 -13.90 -2.55 1.9630398 -0.7375982 -11.9369602 -3.2875982 2
#> 5 1 -14.40 -5.80 -0.7461610 0.5740361 -15.1461610 -5.2259639 2
#> 6 1 -3.60 -1.70 1.1724058 0.9519715 -2.4275942 -0.7480285 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -38275 7025
#> initial value 998.131940
#> iter 2 value 820.132002
#> iter 3 value 808.671749
#> iter 4 value 807.589000
#> iter 5 value 769.808211
#> iter 6 value 761.347358
#> iter 7 value 759.964884
#> iter 8 value 759.935731
#> iter 9 value 759.935680
#> iter 10 value 759.935667
#> iter 10 value 759.935656
#> iter 10 value 759.935656
#> final value 759.935656
#> converged
#> This is Run number 4
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1651308 0.04473541 -0.38486924 -12.555265 1
#> 2 1 -0.95 -2.35 1.0457067 -0.56572294 0.09570666 -2.915723 1
#> 3 1 -6.20 -2.30 0.2653277 0.21907004 -5.93467227 -2.080930 2
#> 4 1 -13.90 -2.55 -0.4685129 0.47136596 -14.36851288 -2.078634 2
#> 5 1 -14.40 -5.80 1.5752600 2.73346135 -12.82473995 -3.066539 2
#> 6 1 -3.60 -1.70 -0.3584104 0.55026311 -3.95841043 -1.149737 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -39625 8000
#> initial value 998.131940
#> iter 2 value 794.188083
#> iter 3 value 778.031063
#> iter 4 value 777.087469
#> iter 5 value 743.540679
#> iter 6 value 734.976004
#> iter 7 value 733.845920
#> iter 8 value 733.827251
#> iter 9 value 733.827233
#> iter 9 value 733.827230
#> iter 9 value 733.827220
#> final value 733.827220
#> converged
#> This is Run number 5
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5668505 1.9385048 -1.116850 -10.6614952 1
#> 2 1 -0.95 -2.35 -1.0846610 0.5273078 -2.034661 -1.8226922 2
#> 3 1 -6.20 -2.30 -1.1667192 -0.3741714 -7.366719 -2.6741714 2
#> 4 1 -13.90 -2.55 -0.1146248 1.0349357 -14.014625 -1.5150643 2
#> 5 1 -14.40 -5.80 -0.4668516 2.2256308 -14.866852 -3.5743692 2
#> 6 1 -3.60 -1.70 0.2743071 2.4364835 -3.325693 0.7364835 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -36600 5775
#> initial value 998.131940
#> iter 2 value 849.190980
#> iter 3 value 842.712950
#> iter 4 value 841.936546
#> iter 5 value 799.442275
#> iter 6 value 791.541423
#> iter 7 value 789.904678
#> iter 8 value 789.870085
#> iter 9 value 789.869999
#> iter 9 value 789.869999
#> iter 9 value 789.869999
#> final value 789.869999
#> converged
#> This is Run number 6
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1867229 -1.3282405 -0.3632771 -13.92824045 1
#> 2 1 -0.95 -2.35 -0.7120267 0.4058905 -1.6620267 -1.94410949 1
#> 3 1 -6.20 -2.30 0.9499792 1.3408087 -5.2500208 -0.95919130 2
#> 4 1 -13.90 -2.55 -0.6068414 -0.2863894 -14.5068414 -2.83638939 2
#> 5 1 -14.40 -5.80 0.2791787 0.1775473 -14.1208213 -5.62245268 2
#> 6 1 -3.60 -1.70 -0.4503255 1.6392219 -4.0503255 -0.06077805 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -40050 6300
#> initial value 998.131940
#> iter 2 value 797.254783
#> iter 3 value 784.067854
#> iter 4 value 781.033483
#> iter 5 value 748.988742
#> iter 6 value 740.229226
#> iter 7 value 738.865229
#> iter 8 value 738.831723
#> iter 9 value 738.831657
#> iter 9 value 738.831649
#> iter 9 value 738.831643
#> final value 738.831643
#> converged
#> This is Run number 7
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.21350661 -0.0899883 -0.3364934 -12.689988 1
#> 2 1 -0.95 -2.35 2.12381588 -0.2254029 1.1738159 -2.575403 1
#> 3 1 -6.20 -2.30 4.10025765 0.4750744 -2.0997424 -1.824926 2
#> 4 1 -13.90 -2.55 -0.41310328 -0.6352374 -14.3131033 -3.185237 2
#> 5 1 -14.40 -5.80 0.05799517 -1.3854798 -14.3420048 -7.185480 2
#> 6 1 -3.60 -1.70 2.15245815 0.5629682 -1.4475418 -1.137032 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5760 -37400 6900
#> initial value 998.131940
#> iter 2 value 833.324198
#> iter 3 value 821.238217
#> iter 4 value 819.048965
#> iter 5 value 779.096282
#> iter 6 value 770.853182
#> iter 7 value 769.477617
#> iter 8 value 769.450544
#> iter 9 value 769.450502
#> iter 9 value 769.450491
#> iter 9 value 769.450486
#> final value 769.450486
#> converged
#> This is Run number 8
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5798834 -0.3211425 0.02988338 -12.9211425 1
#> 2 1 -0.95 -2.35 -0.6568726 2.9615102 -1.60687260 0.6115102 2
#> 3 1 -6.20 -2.30 1.0462290 -0.8025417 -5.15377097 -3.1025417 2
#> 4 1 -13.90 -2.55 1.9432565 -0.5925105 -11.95674349 -3.1425105 2
#> 5 1 -14.40 -5.80 -0.2125311 -0.5395650 -14.61253107 -6.3395650 2
#> 6 1 -3.60 -1.70 0.5850380 0.8600823 -3.01496199 -0.8399177 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39500 7725
#> initial value 998.131940
#> iter 2 value 797.555745
#> iter 3 value 783.435479
#> iter 4 value 783.002682
#> iter 5 value 748.858861
#> iter 6 value 740.221327
#> iter 7 value 739.023456
#> iter 8 value 739.001304
#> iter 9 value 739.001293
#> iter 9 value 739.001288
#> iter 10 value 739.001265
#> iter 11 value 739.001253
#> iter 11 value 739.001253
#> iter 11 value 739.001250
#> final value 739.001250
#> converged
#> This is Run number 9
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.69241378 -0.027102867 -1.242414 -12.6271029 1
#> 2 1 -0.95 -2.35 -0.33240342 0.957319274 -1.282403 -1.3926807 1
#> 3 1 -6.20 -2.30 -0.02159452 0.523861864 -6.221595 -1.7761381 2
#> 4 1 -13.90 -2.55 -0.43976792 2.255627590 -14.339768 -0.2943724 2
#> 5 1 -14.40 -5.80 1.59548064 0.005022084 -12.804519 -5.7949779 2
#> 6 1 -3.60 -1.70 0.36964385 -0.070284512 -3.230356 -1.7702845 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38925 7375
#> initial value 998.131940
#> iter 2 value 808.805881
#> iter 3 value 794.383536
#> iter 4 value 792.492764
#> iter 5 value 756.940395
#> iter 6 value 748.397803
#> iter 7 value 747.136101
#> iter 8 value 747.111451
#> iter 9 value 747.111422
#> iter 9 value 747.111412
#> iter 9 value 747.111406
#> final value 747.111406
#> converged
#> This is Run number 10
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.55377101 -0.06400035 -1.1037710 -12.664000 1
#> 2 1 -0.95 -2.35 0.65046709 1.31960333 -0.2995329 -1.030397 1
#> 3 1 -6.20 -2.30 -0.08514854 -0.35122632 -6.2851485 -2.651226 2
#> 4 1 -13.90 -2.55 -0.24910236 0.41807233 -14.1491024 -2.131928 2
#> 5 1 -14.40 -5.80 1.44398692 0.61195541 -12.9560131 -5.188045 2
#> 6 1 -3.60 -1.70 1.29566396 0.41997169 -2.3043360 -1.280028 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7240 -39850 6400
#> initial value 998.131940
#> iter 2 value 799.047238
#> iter 3 value 789.288368
#> iter 4 value 788.745320
#> iter 5 value 755.304582
#> iter 6 value 746.556906
#> iter 7 value 745.070645
#> iter 8 value 745.032618
#> iter 9 value 745.032529
#> iter 10 value 745.032514
#> iter 10 value 745.032507
#> iter 10 value 745.032499
#> final value 745.032499
#> converged
#> This is Run number 11
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8302687 0.6367215 0.2802687 -11.963278 1
#> 2 1 -0.95 -2.35 0.1713546 -0.6215377 -0.7786454 -2.971538 1
#> 3 1 -6.20 -2.30 0.2922556 0.0418291 -5.9077444 -2.258171 2
#> 4 1 -13.90 -2.55 1.1815540 0.6897143 -12.7184460 -1.860286 2
#> 5 1 -14.40 -5.80 -0.2580984 1.6449478 -14.6580984 -4.155052 2
#> 6 1 -3.60 -1.70 2.0032401 0.0826559 -1.5967599 -1.617344 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5560 -39250 7150
#> initial value 998.131940
#> iter 2 value 805.365550
#> iter 3 value 787.032465
#> iter 4 value 782.361624
#> iter 5 value 748.443105
#> iter 6 value 739.857615
#> iter 7 value 738.659548
#> iter 8 value 738.636756
#> iter 9 value 738.636736
#> iter 9 value 738.636731
#> iter 9 value 738.636727
#> final value 738.636727
#> converged
#> This is Run number 12
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9803801 -0.26153559 -1.5303801 -12.8615356 1
#> 2 1 -0.95 -2.35 1.7419333 0.07796661 0.7919333 -2.2720334 1
#> 3 1 -6.20 -2.30 1.4003382 -0.88584325 -4.7996618 -3.1858432 2
#> 4 1 -13.90 -2.55 -1.4346036 -0.76433179 -15.3346036 -3.3143318 2
#> 5 1 -14.40 -5.80 -0.6871762 -1.84393126 -15.0871762 -7.6439313 2
#> 6 1 -3.60 -1.70 3.1893690 1.48324819 -0.4106310 -0.2167518 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -38575 6775
#> initial value 998.131940
#> iter 2 value 816.882836
#> iter 3 value 806.574919
#> iter 4 value 805.890778
#> iter 5 value 768.813677
#> iter 6 value 760.282612
#> iter 7 value 758.832693
#> iter 8 value 758.799819
#> iter 9 value 758.799752
#> iter 10 value 758.799736
#> iter 10 value 758.799726
#> iter 10 value 758.799725
#> final value 758.799725
#> converged
#> This is Run number 13
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1991772 1.1511615 -0.74917718 -11.448838 1
#> 2 1 -0.95 -2.35 0.9329473 0.3775952 -0.01705267 -1.972405 1
#> 3 1 -6.20 -2.30 1.8494722 -0.5189996 -4.35052776 -2.819000 2
#> 4 1 -13.90 -2.55 0.1553253 0.6869012 -13.74467470 -1.863099 2
#> 5 1 -14.40 -5.80 2.9140428 2.1088163 -11.48595724 -3.691184 2
#> 6 1 -3.60 -1.70 0.9493834 -0.4533498 -2.65061659 -2.153350 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -38225 7225
#> initial value 998.131940
#> iter 2 value 819.997689
#> iter 3 value 805.307244
#> iter 4 value 802.513743
#> iter 5 value 765.124055
#> iter 6 value 756.700421
#> iter 7 value 755.405431
#> iter 8 value 755.380579
#> iter 9 value 755.380550
#> iter 9 value 755.380540
#> iter 9 value 755.380535
#> final value 755.380535
#> converged
#> This is Run number 14
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0226271 1.8022229 -1.5726271 -10.7977771 1
#> 2 1 -0.95 -2.35 0.2449677 -0.7119570 -0.7050323 -3.0619570 1
#> 3 1 -6.20 -2.30 -0.3483096 -0.8870686 -6.5483096 -3.1870686 2
#> 4 1 -13.90 -2.55 -0.3558228 1.8516659 -14.2558228 -0.6983341 2
#> 5 1 -14.40 -5.80 1.9414634 3.9030741 -12.4585366 -1.8969259 2
#> 6 1 -3.60 -1.70 0.8671413 2.5681117 -2.7328587 0.8681117 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -38125 7250
#> initial value 998.131940
#> iter 2 value 821.172714
#> iter 3 value 808.367696
#> iter 4 value 806.782637
#> iter 5 value 768.753533
#> iter 6 value 760.339769
#> iter 7 value 759.013804
#> iter 8 value 758.987644
#> iter 9 value 758.987607
#> iter 10 value 758.987595
#> iter 10 value 758.987585
#> iter 10 value 758.987580
#> final value 758.987580
#> converged
#> This is Run number 15
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6697426 -0.2212345 -1.2197426 -12.821234 1
#> 2 1 -0.95 -2.35 0.1329135 -0.1484477 -0.8170865 -2.498448 1
#> 3 1 -6.20 -2.30 1.8040782 -1.1926918 -4.3959218 -3.492692 2
#> 4 1 -13.90 -2.55 -0.2969303 0.4498545 -14.1969303 -2.100146 2
#> 5 1 -14.40 -5.80 -0.8939682 0.1640928 -15.2939682 -5.635907 2
#> 6 1 -3.60 -1.70 -0.9939891 0.3689768 -4.5939891 -1.331023 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -37875 6650
#> initial value 998.131940
#> iter 2 value 827.899993
#> iter 3 value 817.382899
#> iter 4 value 815.958442
#> iter 5 value 777.095544
#> iter 6 value 768.734927
#> iter 7 value 767.282448
#> iter 8 value 767.251137
#> iter 9 value 767.251077
#> iter 9 value 767.251076
#> iter 9 value 767.251076
#> final value 767.251076
#> converged
#> This is Run number 16
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4430095 -0.5300688 -0.9930095 -13.1300688 1
#> 2 1 -0.95 -2.35 3.5029252 -1.1477896 2.5529252 -3.4977896 1
#> 3 1 -6.20 -2.30 1.2878364 1.4547887 -4.9121636 -0.8452113 2
#> 4 1 -13.90 -2.55 2.0919139 -1.2793114 -11.8080861 -3.8293114 2
#> 5 1 -14.40 -5.80 -0.3452620 -0.5455779 -14.7452620 -6.3455779 2
#> 6 1 -3.60 -1.70 -1.0382948 -0.3328220 -4.6382948 -2.0328220 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38700 8425
#> initial value 998.131940
#> iter 2 value 805.632321
#> iter 3 value 787.126143
#> iter 4 value 784.943829
#> iter 5 value 749.005847
#> iter 6 value 740.652192
#> iter 7 value 739.522359
#> iter 8 value 739.506073
#> iter 9 value 739.506060
#> iter 9 value 739.506055
#> iter 9 value 739.506052
#> final value 739.506052
#> converged
#> This is Run number 17
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.10726253 0.1562533 0.5572625 -12.4437467 1
#> 2 1 -0.95 -2.35 -1.03723690 2.4601367 -1.9872369 0.1101367 2
#> 3 1 -6.20 -2.30 0.33340273 0.2966318 -5.8665973 -2.0033682 2
#> 4 1 -13.90 -2.55 0.47342490 1.1619897 -13.4265751 -1.3880103 2
#> 5 1 -14.40 -5.80 -0.04790816 -0.9262372 -14.4479082 -6.7262372 2
#> 6 1 -3.60 -1.70 -0.25237807 0.6792071 -3.8523781 -1.0207929 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6060 -39525 8600
#> initial value 998.131940
#> iter 2 value 791.960827
#> iter 3 value 772.617019
#> iter 4 value 771.139777
#> iter 5 value 737.594100
#> iter 6 value 729.207147
#> iter 7 value 728.147911
#> iter 8 value 728.133621
#> iter 9 value 728.133602
#> iter 9 value 728.133596
#> iter 9 value 728.133596
#> final value 728.133596
#> converged
#> This is Run number 18
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7412233 0.62578691 0.1912233 -11.974213 1
#> 2 1 -0.95 -2.35 0.3224486 0.83719236 -0.6275514 -1.512808 1
#> 3 1 -6.20 -2.30 -1.0891595 -0.07786002 -7.2891595 -2.377860 2
#> 4 1 -13.90 -2.55 -0.6999784 0.43833581 -14.5999784 -2.111664 2
#> 5 1 -14.40 -5.80 -0.9937733 0.84542868 -15.3937733 -4.954571 2
#> 6 1 -3.60 -1.70 0.4503231 -0.52201593 -3.1496769 -2.222016 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -40025 5825
#> initial value 998.131940
#> iter 2 value 798.921328
#> iter 3 value 790.485091
#> iter 4 value 789.657678
#> iter 5 value 756.737560
#> iter 6 value 747.986793
#> iter 7 value 746.352573
#> iter 8 value 746.307171
#> iter 9 value 746.307041
#> iter 10 value 746.307026
#> iter 10 value 746.307026
#> iter 10 value 746.307019
#> final value 746.307019
#> converged
#> This is Run number 19
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5742353 0.2599047 -1.12423532 -12.340095 1
#> 2 1 -0.95 -2.35 0.8716942 1.0253969 -0.07830585 -1.324603 1
#> 3 1 -6.20 -2.30 0.4024112 -0.1901571 -5.79758884 -2.490157 2
#> 4 1 -13.90 -2.55 1.1478203 -0.7324204 -12.75217966 -3.282420 2
#> 5 1 -14.40 -5.80 0.5179299 1.2628388 -13.88207015 -4.537161 2
#> 6 1 -3.60 -1.70 0.2990833 -0.4118175 -3.30091671 -2.111818 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -40250 8050
#> initial value 998.131940
#> iter 2 value 784.410953
#> iter 3 value 763.207399
#> iter 4 value 759.363723
#> iter 5 value 728.629462
#> iter 6 value 720.229731
#> iter 7 value 719.188904
#> iter 8 value 719.172593
#> iter 8 value 719.172586
#> final value 719.172586
#> converged
#> This is Run number 20
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.54093200 0.9146525 0.99093200 -11.6853475 1
#> 2 1 -0.95 -2.35 0.99359644 0.8103119 0.04359644 -1.5396881 1
#> 3 1 -6.20 -2.30 -0.05574717 3.6530462 -6.25574717 1.3530462 2
#> 4 1 -13.90 -2.55 1.14689252 0.3959909 -12.75310748 -2.1540091 2
#> 5 1 -14.40 -5.80 -0.29085079 0.6199654 -14.69085079 -5.1800346 2
#> 6 1 -3.60 -1.70 -0.57138927 1.2125393 -4.17138927 -0.4874607 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38500 6550
#> initial value 998.131940
#> iter 2 value 819.663167
#> iter 3 value 806.484485
#> iter 4 value 803.481753
#> iter 5 value 766.853816
#> iter 6 value 758.331166
#> iter 7 value 756.931409
#> iter 8 value 756.900884
#> iter 9 value 756.900831
#> iter 9 value 756.900822
#> iter 9 value 756.900817
#> final value 756.900817
#> converged
#> This is Run number 21
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1726579 -1.3164440 2.622657902 -13.9164440 1
#> 2 1 -0.95 -2.35 0.9532956 3.6710337 0.003295594 1.3210337 2
#> 3 1 -6.20 -2.30 0.6409443 0.4491905 -5.559055733 -1.8508095 2
#> 4 1 -13.90 -2.55 -0.3810352 2.1951681 -14.281035155 -0.3548319 2
#> 5 1 -14.40 -5.80 1.5795551 -0.3248330 -12.820444855 -6.1248330 2
#> 6 1 -3.60 -1.70 -0.4157202 -0.5185339 -4.015720176 -2.2185339 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -39550 7375
#> initial value 998.131940
#> iter 2 value 799.220577
#> iter 3 value 784.729741
#> iter 4 value 783.181163
#> iter 5 value 749.406678
#> iter 6 value 740.779257
#> iter 7 value 739.551151
#> iter 8 value 739.526731
#> iter 9 value 739.526702
#> iter 9 value 739.526693
#> iter 9 value 739.526686
#> final value 739.526686
#> converged
#> This is Run number 22
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8175021 -0.35435672 -1.367502 -12.954357 1
#> 2 1 -0.95 -2.35 -0.1995796 -0.61567055 -1.149580 -2.965671 1
#> 3 1 -6.20 -2.30 0.7204438 0.23624759 -5.479556 -2.063752 2
#> 4 1 -13.90 -2.55 1.8926614 -0.02072729 -12.007339 -2.570727 2
#> 5 1 -14.40 -5.80 -0.2718300 0.18629880 -14.671830 -5.613701 2
#> 6 1 -3.60 -1.70 -0.6245241 0.21125305 -4.224524 -1.488747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5600 -37200 7575
#> initial value 998.131940
#> iter 2 value 832.190865
#> iter 3 value 818.820408
#> iter 4 value 816.918318
#> iter 5 value 776.346371
#> iter 6 value 768.166574
#> iter 7 value 766.883717
#> iter 8 value 766.861318
#> iter 9 value 766.861291
#> iter 9 value 766.861281
#> iter 9 value 766.861276
#> final value 766.861276
#> converged
#> This is Run number 23
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.23997973 1.6529340 -0.3100203 -10.947066 1
#> 2 1 -0.95 -2.35 -0.35775476 -1.0901106 -1.3077548 -3.440111 1
#> 3 1 -6.20 -2.30 0.05300973 -1.1033464 -6.1469903 -3.403346 2
#> 4 1 -13.90 -2.55 1.55715428 1.0464371 -12.3428457 -1.503563 2
#> 5 1 -14.40 -5.80 1.06540419 0.6167304 -13.3345958 -5.183270 2
#> 6 1 -3.60 -1.70 -0.29567605 0.3535731 -3.8956761 -1.346427 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -39025 6950
#> initial value 998.131940
#> iter 2 value 809.832251
#> iter 3 value 794.516541
#> iter 4 value 791.150581
#> iter 5 value 756.230383
#> iter 6 value 747.646775
#> iter 7 value 746.359738
#> iter 8 value 746.333251
#> iter 9 value 746.333218
#> iter 9 value 746.333210
#> iter 9 value 746.333205
#> final value 746.333205
#> converged
#> This is Run number 24
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5811512 -0.6668047 -1.131151 -13.2668047 1
#> 2 1 -0.95 -2.35 2.3536173 -1.0546874 1.403617 -3.4046874 1
#> 3 1 -6.20 -2.30 -1.0869926 -0.5082091 -7.286993 -2.8082091 2
#> 4 1 -13.90 -2.55 0.5573746 2.3065882 -13.342625 -0.2434118 2
#> 5 1 -14.40 -5.80 -0.5445224 0.0458446 -14.944522 -5.7541554 2
#> 6 1 -3.60 -1.70 -0.3383747 -0.7048156 -3.938375 -2.4048156 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38900 6875
#> initial value 998.131940
#> iter 2 value 811.861737
#> iter 3 value 799.578196
#> iter 4 value 797.953502
#> iter 5 value 762.142990
#> iter 6 value 753.563423
#> iter 7 value 752.195332
#> iter 8 value 752.165387
#> iter 9 value 752.165337
#> iter 10 value 752.165325
#> iter 10 value 752.165317
#> iter 10 value 752.165317
#> final value 752.165317
#> converged
#> This is Run number 25
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.79506340 2.9684872 0.2450634 -9.6315128 1
#> 2 1 -0.95 -2.35 0.02059948 4.0962295 -0.9294005 1.7462295 2
#> 3 1 -6.20 -2.30 -0.89827309 -0.2988247 -7.0982731 -2.5988247 2
#> 4 1 -13.90 -2.55 1.85670394 -0.5479160 -12.0432961 -3.0979160 2
#> 5 1 -14.40 -5.80 0.33733135 0.2319431 -14.0626686 -5.5680569 2
#> 6 1 -3.60 -1.70 1.80807202 2.1504539 -1.7919280 0.4504539 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -38200 6400
#> initial value 998.131940
#> iter 2 value 824.772414
#> iter 3 value 811.610414
#> iter 4 value 808.317614
#> iter 5 value 770.861084
#> iter 6 value 762.384077
#> iter 7 value 760.960246
#> iter 8 value 760.929323
#> iter 9 value 760.929266
#> iter 9 value 760.929257
#> iter 9 value 760.929252
#> final value 760.929252
#> converged
#> This is Run number 26
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.61494977 0.7730959 0.06494977 -11.826904 1
#> 2 1 -0.95 -2.35 1.88643832 0.6808709 0.93643832 -1.669129 1
#> 3 1 -6.20 -2.30 -0.86961688 -0.1904128 -7.06961688 -2.490413 2
#> 4 1 -13.90 -2.55 -0.05374765 0.7616439 -13.95374765 -1.788356 2
#> 5 1 -14.40 -5.80 3.47362298 1.5059658 -10.92637702 -4.294034 2
#> 6 1 -3.60 -1.70 0.28917639 -1.3190910 -3.31082361 -3.019091 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -38275 5925
#> initial value 998.131940
#> iter 2 value 825.848063
#> iter 3 value 815.246076
#> iter 4 value 812.696404
#> iter 5 value 775.260391
#> iter 6 value 766.794316
#> iter 7 value 765.220969
#> iter 8 value 765.183547
#> iter 9 value 765.183455
#> iter 10 value 765.183442
#> iter 10 value 765.183442
#> iter 10 value 765.183438
#> final value 765.183438
#> converged
#> This is Run number 27
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.17428232 -0.5063131 -0.3757177 -13.1063131 1
#> 2 1 -0.95 -2.35 0.59503521 0.4532163 -0.3549648 -1.8967837 1
#> 3 1 -6.20 -2.30 -0.80878323 2.8184548 -7.0087832 0.5184548 2
#> 4 1 -13.90 -2.55 1.16638698 -1.1685989 -12.7336130 -3.7185989 2
#> 5 1 -14.40 -5.80 3.87828296 -0.5075608 -10.5217170 -6.3075608 2
#> 6 1 -3.60 -1.70 0.05482436 1.8947469 -3.5451756 0.1947469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -37525 6375
#> initial value 998.131940
#> iter 2 value 833.922833
#> iter 3 value 825.513174
#> iter 4 value 824.798810
#> iter 5 value 784.717063
#> iter 6 value 776.469774
#> iter 7 value 774.919701
#> iter 8 value 774.885346
#> iter 9 value 774.885266
#> iter 9 value 774.885264
#> iter 9 value 774.885264
#> final value 774.885264
#> converged
#> This is Run number 28
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.009285943 0.99401803 -0.5592859 -11.6059820 1
#> 2 1 -0.95 -2.35 0.292396581 0.18369436 -0.6576034 -2.1663056 1
#> 3 1 -6.20 -2.30 -1.115241992 0.01880581 -7.3152420 -2.2811942 2
#> 4 1 -13.90 -2.55 2.386206195 2.16271800 -11.5137938 -0.3872820 2
#> 5 1 -14.40 -5.80 0.733583378 0.96497297 -13.6664166 -4.8350270 2
#> 6 1 -3.60 -1.70 0.401342416 0.96390485 -3.1986576 -0.7360952 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38750 8175
#> initial value 998.131940
#> iter 2 value 806.438136
#> iter 3 value 790.250129
#> iter 4 value 789.046565
#> iter 5 value 752.928739
#> iter 6 value 744.477324
#> iter 7 value 743.317181
#> iter 8 value 743.298959
#> iter 9 value 743.298945
#> iter 9 value 743.298942
#> iter 10 value 743.298931
#> iter 10 value 743.298923
#> iter 10 value 743.298922
#> final value 743.298922
#> converged
#> This is Run number 29
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7471286 -0.3855214 1.1971286 -12.9855214 1
#> 2 1 -0.95 -2.35 0.1612026 1.2885028 -0.7887974 -1.0614972 1
#> 3 1 -6.20 -2.30 3.1399183 0.7451406 -3.0600817 -1.5548594 2
#> 4 1 -13.90 -2.55 1.1562691 1.1418581 -12.7437309 -1.4081419 2
#> 5 1 -14.40 -5.80 -0.2553048 -0.4954830 -14.6553048 -6.2954830 2
#> 6 1 -3.60 -1.70 1.7257312 0.8319119 -1.8742688 -0.8680881 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -36675 6825
#> initial value 998.131940
#> iter 2 value 843.431492
#> iter 3 value 832.639176
#> iter 4 value 830.764674
#> iter 5 value 788.737420
#> iter 6 value 780.709120
#> iter 7 value 779.326526
#> iter 8 value 779.300299
#> iter 9 value 779.300257
#> iter 9 value 779.300256
#> iter 9 value 779.300256
#> final value 779.300256
#> converged
#> This is Run number 30
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4583561 -0.4276330 -1.008356 -13.027633 1
#> 2 1 -0.95 -2.35 -0.9055229 -0.1672029 -1.855523 -2.517203 1
#> 3 1 -6.20 -2.30 1.7038551 0.7256820 -4.496145 -1.574318 2
#> 4 1 -13.90 -2.55 -0.7621098 -0.4771581 -14.662110 -3.027158 2
#> 5 1 -14.40 -5.80 -0.3998774 -1.0933774 -14.799877 -6.893377 2
#> 6 1 -3.60 -1.70 1.6273573 0.1763657 -1.972643 -1.523634 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -38075 6375
#> initial value 998.131940
#> iter 2 value 826.535088
#> iter 3 value 815.752278
#> iter 4 value 813.745311
#> iter 5 value 775.608465
#> iter 6 value 767.196971
#> iter 7 value 765.709509
#> iter 8 value 765.676337
#> iter 9 value 765.676270
#> iter 9 value 765.676260
#> iter 9 value 765.676254
#> final value 765.676254
#> converged
#> This is Run number 31
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0695231 0.2012381 -1.619523 -12.3987619 1
#> 2 1 -0.95 -2.35 -0.3692137 1.7454102 -1.319214 -0.6045898 2
#> 3 1 -6.20 -2.30 0.9046795 1.4778487 -5.295320 -0.8221513 2
#> 4 1 -13.90 -2.55 -0.2933849 0.7417986 -14.193385 -1.8082014 2
#> 5 1 -14.40 -5.80 -0.6282223 1.8206628 -15.028222 -3.9793372 2
#> 6 1 -3.60 -1.70 0.7008495 -0.9524986 -2.899151 -2.6524986 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37975 6875
#> initial value 998.131940
#> iter 2 value 825.239839
#> iter 3 value 814.469941
#> iter 4 value 813.367835
#> iter 5 value 774.710702
#> iter 6 value 766.320084
#> iter 7 value 764.901373
#> iter 8 value 764.871231
#> iter 9 value 764.871175
#> iter 10 value 764.871161
#> iter 10 value 764.871151
#> iter 10 value 764.871146
#> final value 764.871146
#> converged
#> This is Run number 32
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2923237 -0.34185310 -0.2576763 -12.94185310 1
#> 2 1 -0.95 -2.35 0.1778100 2.28439972 -0.7721900 -0.06560028 2
#> 3 1 -6.20 -2.30 4.6585126 0.50816742 -1.5414874 -1.79183258 1
#> 4 1 -13.90 -2.55 2.6096463 0.06879165 -11.2903537 -2.48120835 2
#> 5 1 -14.40 -5.80 -0.2451368 -0.42604177 -14.6451368 -6.22604177 2
#> 6 1 -3.60 -1.70 1.2610084 -0.99274356 -2.3389916 -2.69274356 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38150 5800
#> initial value 998.131940
#> iter 2 value 827.981080
#> iter 3 value 819.282063
#> iter 4 value 817.639860
#> iter 5 value 779.580434
#> iter 6 value 771.185328
#> iter 7 value 769.529829
#> iter 8 value 769.489814
#> iter 9 value 769.489708
#> iter 10 value 769.489695
#> iter 10 value 769.489693
#> iter 10 value 769.489692
#> final value 769.489692
#> converged
#> This is Run number 33
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7820398 -0.3618176 -1.332040 -12.9618176 1
#> 2 1 -0.95 -2.35 -0.2823878 0.4905537 -1.232388 -1.8594463 1
#> 3 1 -6.20 -2.30 0.6124959 0.2771269 -5.587504 -2.0228731 2
#> 4 1 -13.90 -2.55 1.1618612 0.4721477 -12.738139 -2.0778523 2
#> 5 1 -14.40 -5.80 2.9320682 -0.3157078 -11.467932 -6.1157078 2
#> 6 1 -3.60 -1.70 -0.5046445 2.4571157 -4.104644 0.7571157 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37900 6850
#> initial value 998.131940
#> iter 2 value 826.616061
#> iter 3 value 814.587727
#> iter 4 value 812.582007
#> iter 5 value 773.985393
#> iter 6 value 765.615980
#> iter 7 value 764.226528
#> iter 8 value 764.197877
#> iter 9 value 764.197830
#> iter 9 value 764.197819
#> iter 9 value 764.197813
#> final value 764.197813
#> converged
#> This is Run number 34
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.35318374 1.71399735 0.8031837 -10.88600265 1
#> 2 1 -0.95 -2.35 -0.05992435 -0.10723221 -1.0099244 -2.45723221 1
#> 3 1 -6.20 -2.30 0.09335095 -1.19775312 -6.1066491 -3.49775312 2
#> 4 1 -13.90 -2.55 -0.59008289 0.74789339 -14.4900829 -1.80210661 2
#> 5 1 -14.40 -5.80 1.81945873 0.01755771 -12.5805413 -5.78244229 2
#> 6 1 -3.60 -1.70 -0.12606651 1.78929845 -3.7260665 0.08929845 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38325 7575
#> initial value 998.131940
#> iter 2 value 816.457874
#> iter 3 value 801.948179
#> iter 4 value 800.077130
#> iter 5 value 762.770038
#> iter 6 value 754.342467
#> iter 7 value 753.083401
#> iter 8 value 753.060307
#> iter 9 value 753.060281
#> iter 9 value 753.060272
#> iter 9 value 753.060266
#> final value 753.060266
#> converged
#> This is Run number 35
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.14043048 1.39313651 -0.4095695 -11.2068635 1
#> 2 1 -0.95 -2.35 -0.73092421 2.68732915 -1.6809242 0.3373292 2
#> 3 1 -6.20 -2.30 -0.15294274 1.21610800 -6.3529427 -1.0838920 2
#> 4 1 -13.90 -2.55 -0.04897067 1.62698452 -13.9489707 -0.9230155 2
#> 5 1 -14.40 -5.80 1.84091168 0.11293400 -12.5590883 -5.6870660 2
#> 6 1 -3.60 -1.70 -0.72173644 -0.04155647 -4.3217364 -1.7415565 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38675 7275
#> initial value 998.131940
#> iter 2 value 813.146036
#> iter 3 value 798.593452
#> iter 4 value 796.234509
#> iter 5 value 760.058109
#> iter 6 value 751.554155
#> iter 7 value 750.274208
#> iter 8 value 750.249141
#> iter 9 value 750.249111
#> iter 9 value 750.249101
#> iter 9 value 750.249096
#> final value 750.249096
#> converged
#> This is Run number 36
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.54236870 1.37120574 -1.092369 -11.228794 1
#> 2 1 -0.95 -2.35 -0.13553929 -1.50755110 -1.085539 -3.857551 1
#> 3 1 -6.20 -2.30 -0.46534926 -0.08382678 -6.665349 -2.383827 2
#> 4 1 -13.90 -2.55 -0.07478104 0.78998504 -13.974781 -1.760015 2
#> 5 1 -14.40 -5.80 0.62893248 0.12093493 -13.771068 -5.679065 2
#> 6 1 -3.60 -1.70 -0.47623471 -0.68165571 -4.076235 -2.381656 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -37200 6375
#> initial value 998.131940
#> iter 2 value 838.701786
#> iter 3 value 828.804108
#> iter 4 value 827.012125
#> iter 5 value 786.387129
#> iter 6 value 778.216387
#> iter 7 value 776.731959
#> iter 8 value 776.700938
#> iter 9 value 776.700877
#> iter 9 value 776.700876
#> iter 9 value 776.700876
#> final value 776.700876
#> converged
#> This is Run number 37
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7042745 1.71020923 1.1542745 -10.8897908 1
#> 2 1 -0.95 -2.35 0.8188401 1.73055549 -0.1311599 -0.6194445 1
#> 3 1 -6.20 -2.30 0.8142049 0.61972236 -5.3857951 -1.6802776 2
#> 4 1 -13.90 -2.55 1.5539823 2.02942975 -12.3460177 -0.5205703 2
#> 5 1 -14.40 -5.80 0.2413219 -0.01021182 -14.1586781 -5.8102118 2
#> 6 1 -3.60 -1.70 -1.1351223 1.98439698 -4.7351223 0.2843970 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38300 5875
#> initial value 998.131940
#> iter 2 value 825.550793
#> iter 3 value 816.241328
#> iter 4 value 814.381273
#> iter 5 value 776.815424
#> iter 6 value 768.371424
#> iter 7 value 766.748122
#> iter 8 value 766.708831
#> iter 9 value 766.708730
#> iter 10 value 766.708718
#> iter 10 value 766.708715
#> iter 10 value 766.708711
#> final value 766.708711
#> converged
#> This is Run number 38
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7138098 -0.6272689 0.1638098 -13.227269 1
#> 2 1 -0.95 -2.35 1.1214789 -0.3768925 0.1714789 -2.726892 1
#> 3 1 -6.20 -2.30 -0.7095841 0.6286292 -6.9095841 -1.671371 2
#> 4 1 -13.90 -2.55 0.6902177 -1.0113477 -13.2097823 -3.561348 2
#> 5 1 -14.40 -5.80 1.0391582 -0.3155666 -13.3608418 -6.115567 2
#> 6 1 -3.60 -1.70 4.6394236 0.6673716 1.0394236 -1.032628 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38325 6650
#> initial value 998.131940
#> iter 2 value 821.529415
#> iter 3 value 810.144082
#> iter 4 value 808.364363
#> iter 5 value 770.894356
#> iter 6 value 762.425153
#> iter 7 value 760.993309
#> iter 8 value 760.961861
#> iter 9 value 760.961803
#> iter 9 value 760.961803
#> iter 9 value 760.961803
#> final value 760.961803
#> converged
#> This is Run number 39
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.78675832 0.06521298 -1.33675832 -12.5347870 1
#> 2 1 -0.95 -2.35 0.96785957 2.19000495 0.01785957 -0.1599950 1
#> 3 1 -6.20 -2.30 -1.04345527 0.19961485 -7.24345527 -2.1003852 2
#> 4 1 -13.90 -2.55 -0.04306056 -0.68188404 -13.94306056 -3.2318840 2
#> 5 1 -14.40 -5.80 3.13787860 -0.01945734 -11.26212140 -5.8194573 2
#> 6 1 -3.60 -1.70 0.29463320 1.46263966 -3.30536680 -0.2373603 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37625 7150
#> initial value 998.131940
#> iter 2 value 828.350273
#> iter 3 value 818.368201
#> iter 4 value 818.098898
#> iter 5 value 778.265521
#> iter 6 value 769.940285
#> iter 7 value 768.529884
#> iter 8 value 768.500721
#> iter 9 value 768.500664
#> iter 10 value 768.500647
#> iter 10 value 768.500637
#> iter 10 value 768.500631
#> final value 768.500631
#> converged
#> This is Run number 40
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 5.64420497 -0.3499432 5.094205 -12.9499432 1
#> 2 1 -0.95 -2.35 -0.87913942 -0.1768537 -1.829139 -2.5268537 1
#> 3 1 -6.20 -2.30 0.18467297 1.7994440 -6.015327 -0.5005560 2
#> 4 1 -13.90 -2.55 0.55369332 1.8287463 -13.346307 -0.7212537 2
#> 5 1 -14.40 -5.80 0.40074217 0.1881833 -13.999258 -5.6118167 2
#> 6 1 -3.60 -1.70 -0.05689137 -0.7171636 -3.656891 -2.4171636 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5780 -37300 7100
#> initial value 998.131940
#> iter 2 value 833.572147
#> iter 3 value 821.535543
#> iter 4 value 819.669924
#> iter 5 value 779.354791
#> iter 6 value 771.141273
#> iter 7 value 769.789226
#> iter 8 value 769.763318
#> iter 9 value 769.763279
#> iter 9 value 769.763268
#> iter 9 value 769.763262
#> final value 769.763262
#> converged
#> This is Run number 41
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.71344109 -0.61904602 0.1634411 -13.2190460 1
#> 2 1 -0.95 -2.35 -0.77153748 2.68346729 -1.7215375 0.3334673 2
#> 3 1 -6.20 -2.30 0.77589563 1.10408139 -5.4241044 -1.1959186 2
#> 4 1 -13.90 -2.55 2.34094934 1.97225981 -11.5590507 -0.5777402 2
#> 5 1 -14.40 -5.80 -1.14422438 1.35972356 -15.5442244 -4.4402764 2
#> 6 1 -3.60 -1.70 0.06537586 0.04048977 -3.5346241 -1.6595102 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6540 -38450 6950
#> initial value 998.131940
#> iter 2 value 817.889984
#> iter 3 value 806.904123
#> iter 4 value 806.075294
#> iter 5 value 768.711924
#> iter 6 value 760.208173
#> iter 7 value 758.803017
#> iter 8 value 758.772441
#> iter 9 value 758.772384
#> iter 10 value 758.772369
#> iter 10 value 758.772359
#> iter 10 value 758.772359
#> final value 758.772359
#> converged
#> This is Run number 42
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.66879038 0.4249742 0.1187904 -12.1750258 1
#> 2 1 -0.95 -2.35 1.27022437 -0.3186559 0.3202244 -2.6686559 1
#> 3 1 -6.20 -2.30 3.49196275 0.4859582 -2.7080373 -1.8140418 2
#> 4 1 -13.90 -2.55 0.06579049 0.8237347 -13.8342095 -1.7262653 2
#> 5 1 -14.40 -5.80 -0.35180520 -0.9315576 -14.7518052 -6.7315576 2
#> 6 1 -3.60 -1.70 -0.10000316 1.5322635 -3.7000032 -0.1677365 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -39650 7725
#> initial value 998.131940
#> iter 2 value 795.642293
#> iter 3 value 779.625121
#> iter 4 value 778.030535
#> iter 5 value 744.673312
#> iter 6 value 736.094145
#> iter 7 value 734.934048
#> iter 8 value 734.913266
#> iter 8 value 734.913257
#> final value 734.913257
#> converged
#> This is Run number 43
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.79728459 0.6615376 1.2472846 -11.9384624 1
#> 2 1 -0.95 -2.35 0.69384936 0.7528065 -0.2561506 -1.5971935 1
#> 3 1 -6.20 -2.30 0.09488667 -0.2946189 -6.1051133 -2.5946189 2
#> 4 1 -13.90 -2.55 -0.17879059 0.2140843 -14.0787906 -2.3359157 2
#> 5 1 -14.40 -5.80 0.20991343 2.4000887 -14.1900866 -3.3999113 2
#> 6 1 -3.60 -1.70 0.80539326 0.9928431 -2.7946067 -0.7071569 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -39925 6900
#> initial value 998.131940
#> iter 2 value 796.234974
#> iter 3 value 780.987785
#> iter 4 value 777.914120
#> iter 5 value 745.620412
#> iter 6 value 736.936690
#> iter 7 value 735.696435
#> iter 8 value 735.669800
#> iter 9 value 735.669767
#> iter 9 value 735.669760
#> iter 9 value 735.669756
#> final value 735.669756
#> converged
#> This is Run number 44
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.15137793 -0.2996835 1.601378 -12.8996835 1
#> 2 1 -0.95 -2.35 2.20135275 2.6315006 1.251353 0.2815006 1
#> 3 1 -6.20 -2.30 -0.44624093 1.2011576 -6.646241 -1.0988424 2
#> 4 1 -13.90 -2.55 -0.92385415 0.3782121 -14.823854 -2.1717879 2
#> 5 1 -14.40 -5.80 0.75980472 -0.1540351 -13.640195 -5.9540351 2
#> 6 1 -3.60 -1.70 -0.01342134 0.6343489 -3.613421 -1.0656511 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -39325 7200
#> initial value 998.131940
#> iter 2 value 803.937680
#> iter 3 value 786.970750
#> iter 4 value 783.227340
#> iter 5 value 749.361634
#> iter 6 value 740.778429
#> iter 7 value 739.562344
#> iter 8 value 739.538702
#> iter 9 value 739.538679
#> iter 9 value 739.538673
#> iter 9 value 739.538669
#> final value 739.538669
#> converged
#> This is Run number 45
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2268981 0.52156093 1.6768981 -12.078439 1
#> 2 1 -0.95 -2.35 1.1853668 0.57665505 0.2353668 -1.773345 1
#> 3 1 -6.20 -2.30 1.8662031 -1.16877987 -4.3337969 -3.468780 2
#> 4 1 -13.90 -2.55 1.8871877 0.26783324 -12.0128123 -2.282167 2
#> 5 1 -14.40 -5.80 2.1544772 -0.06336121 -12.2455228 -5.863361 2
#> 6 1 -3.60 -1.70 -0.8812035 -0.01736191 -4.4812035 -1.717362 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6740 -38750 6250
#> initial value 998.131940
#> iter 2 value 816.998406
#> iter 3 value 807.551852
#> iter 4 value 806.444364
#> iter 5 value 769.928505
#> iter 6 value 761.376496
#> iter 7 value 759.822928
#> iter 8 value 759.785233
#> iter 9 value 759.785144
#> iter 10 value 759.785131
#> iter 10 value 759.785124
#> iter 10 value 759.785122
#> final value 759.785122
#> converged
#> This is Run number 46
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0752339 3.5760596 1.5252339 -9.0239404 1
#> 2 1 -0.95 -2.35 0.8326241 -0.7056624 -0.1173759 -3.0556624 1
#> 3 1 -6.20 -2.30 -1.2166153 1.7291134 -7.4166153 -0.5708866 2
#> 4 1 -13.90 -2.55 0.6362095 1.3768847 -13.2637905 -1.1731153 2
#> 5 1 -14.40 -5.80 -0.9054315 0.3000937 -15.3054315 -5.4999063 2
#> 6 1 -3.60 -1.70 0.2473169 1.1548039 -3.3526831 -0.5451961 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38300 7300
#> initial value 998.131940
#> iter 2 value 818.263020
#> iter 3 value 805.890818
#> iter 4 value 804.812583
#> iter 5 value 767.149205
#> iter 6 value 758.688534
#> iter 7 value 757.361049
#> iter 8 value 757.334486
#> iter 9 value 757.334446
#> iter 10 value 757.334433
#> iter 10 value 757.334423
#> iter 10 value 757.334416
#> final value 757.334416
#> converged
#> This is Run number 47
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.002738357 -0.10609074 -0.5527384 -12.70609074 1
#> 2 1 -0.95 -2.35 -1.106705668 2.26787135 -2.0567057 -0.08212865 2
#> 3 1 -6.20 -2.30 0.866482793 0.07076876 -5.3335172 -2.22923124 2
#> 4 1 -13.90 -2.55 -0.515772589 5.44155689 -14.4157726 2.89155689 2
#> 5 1 -14.40 -5.80 2.332070612 -0.22660395 -12.0679294 -6.02660395 2
#> 6 1 -3.60 -1.70 -0.294911813 3.35509553 -3.8949118 1.65509553 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7060 -40100 6825
#> initial value 998.131940
#> iter 2 value 793.158459
#> iter 3 value 781.454262
#> iter 4 value 780.714280
#> iter 5 value 748.201439
#> iter 6 value 739.441585
#> iter 7 value 738.110261
#> iter 8 value 738.078954
#> iter 9 value 738.078898
#> iter 10 value 738.078885
#> iter 10 value 738.078877
#> iter 10 value 738.078870
#> final value 738.078870
#> converged
#> This is Run number 48
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9371712 -0.49542166 2.387171 -13.0954217 1
#> 2 1 -0.95 -2.35 -0.1214152 0.74815949 -1.071415 -1.6018405 1
#> 3 1 -6.20 -2.30 -0.1583219 -0.15883663 -6.358322 -2.4588366 2
#> 4 1 -13.90 -2.55 2.1187215 0.02039968 -11.781279 -2.5296003 2
#> 5 1 -14.40 -5.80 -1.4620323 2.24545905 -15.862032 -3.5545409 2
#> 6 1 -3.60 -1.70 0.5090615 1.32945124 -3.090938 -0.3705488 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -37900 6725
#> initial value 998.131940
#> iter 2 value 827.293699
#> iter 3 value 815.341660
#> iter 4 value 813.156383
#> iter 5 value 774.601331
#> iter 6 value 766.229112
#> iter 7 value 764.822091
#> iter 8 value 764.792688
#> iter 9 value 764.792638
#> iter 9 value 764.792628
#> iter 9 value 764.792622
#> final value 764.792622
#> converged
#> This is Run number 49
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8564031 0.7850111 0.3064031 -11.814989 1
#> 2 1 -0.95 -2.35 0.6465253 -0.2390917 -0.3034747 -2.589092 1
#> 3 1 -6.20 -2.30 0.0358460 3.6958055 -6.1641540 1.395806 2
#> 4 1 -13.90 -2.55 -0.8363841 1.3921845 -14.7363841 -1.157815 2
#> 5 1 -14.40 -5.80 1.3140880 0.0114584 -13.0859120 -5.788542 2
#> 6 1 -3.60 -1.70 0.8793345 -0.8890097 -2.7206655 -2.589010 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38175 7275
#> initial value 998.131940
#> iter 2 value 820.374861
#> iter 3 value 806.770309
#> iter 4 value 804.742841
#> iter 5 value 766.995619
#> iter 6 value 758.579463
#> iter 7 value 757.271294
#> iter 8 value 757.245909
#> iter 9 value 757.245876
#> iter 9 value 757.245865
#> iter 9 value 757.245859
#> final value 757.245859
#> converged
#> This is Run number 50
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0705900 5.1100053 -1.620590 -7.4899947 1
#> 2 1 -0.95 -2.35 -1.1243438 2.1529982 -2.074344 -0.1970018 2
#> 3 1 -6.20 -2.30 -0.4195396 0.3477998 -6.619540 -1.9522002 2
#> 4 1 -13.90 -2.55 0.3434726 1.9679806 -13.556527 -0.5820194 2
#> 5 1 -14.40 -5.80 -0.1494952 -0.4306518 -14.549495 -6.2306518 2
#> 6 1 -3.60 -1.70 0.6583265 1.2582679 -2.941673 -0.4417321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38975 6775
#> initial value 998.131940
#> iter 2 value 811.262900
#> iter 3 value 799.195027
#> iter 4 value 797.529397
#> iter 5 value 761.935076
#> iter 6 value 753.338990
#> iter 7 value 751.954330
#> iter 8 value 751.923408
#> iter 9 value 751.923355
#> iter 10 value 751.923343
#> iter 10 value 751.923335
#> iter 10 value 751.923335
#> final value 751.923335
#> converged
#> This is Run number 51
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1734721 4.0768734 -0.7234721 -8.523127 1
#> 2 1 -0.95 -2.35 -0.5763385 1.2462055 -1.5263385 -1.103794 2
#> 3 1 -6.20 -2.30 0.2401681 -0.1925522 -5.9598319 -2.492552 2
#> 4 1 -13.90 -2.55 -1.0784556 -0.4946384 -14.9784556 -3.044638 2
#> 5 1 -14.40 -5.80 0.9013395 0.6825405 -13.4986605 -5.117459 2
#> 6 1 -3.60 -1.70 2.3287621 -0.6088609 -1.2712379 -2.308861 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38350 6625
#> initial value 998.131940
#> iter 2 value 821.439197
#> iter 3 value 808.514081
#> iter 4 value 805.738817
#> iter 5 value 768.627081
#> iter 6 value 760.142531
#> iter 7 value 758.744908
#> iter 8 value 758.714885
#> iter 9 value 758.714834
#> iter 9 value 758.714825
#> iter 9 value 758.714820
#> final value 758.714820
#> converged
#> This is Run number 52
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.21332141 0.6115616 -0.7633214 -11.988438 1
#> 2 1 -0.95 -2.35 -0.06550073 -0.2540718 -1.0155007 -2.604072 1
#> 3 1 -6.20 -2.30 -0.47778568 0.6458479 -6.6777857 -1.654152 2
#> 4 1 -13.90 -2.55 0.26206233 -0.5363866 -13.6379377 -3.086387 2
#> 5 1 -14.40 -5.80 -1.28305421 -0.9505438 -15.6830542 -6.750544 2
#> 6 1 -3.60 -1.70 -0.03367503 3.4157704 -3.6336750 1.715770 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5600 -37700 6850
#> initial value 998.131940
#> iter 2 value 829.488034
#> iter 3 value 815.880643
#> iter 4 value 812.851747
#> iter 5 value 773.954597
#> iter 6 value 765.620054
#> iter 7 value 764.262927
#> iter 8 value 764.236153
#> iter 9 value 764.236115
#> iter 9 value 764.236106
#> iter 9 value 764.236102
#> final value 764.236102
#> converged
#> This is Run number 53
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5840847 -0.53130286 1.03408467 -13.1313029 1
#> 2 1 -0.95 -2.35 0.9671002 0.57240380 0.01710017 -1.7775962 1
#> 3 1 -6.20 -2.30 1.1787649 -0.04038893 -5.02123513 -2.3403889 2
#> 4 1 -13.90 -2.55 0.5168136 0.74795404 -13.38318641 -1.8020460 2
#> 5 1 -14.40 -5.80 0.0269467 2.70764331 -14.37305330 -3.0923567 2
#> 6 1 -3.60 -1.70 2.1059306 0.91435411 -1.49406938 -0.7856459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -38500 7325
#> initial value 998.131940
#> iter 2 value 815.434675
#> iter 3 value 800.680455
#> iter 4 value 798.200804
#> iter 5 value 761.549803
#> iter 6 value 753.081569
#> iter 7 value 751.804646
#> iter 8 value 751.780141
#> iter 9 value 751.780113
#> iter 9 value 751.780103
#> iter 9 value 751.780098
#> final value 751.780098
#> converged
#> This is Run number 54
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1226000 0.48452969 -1.6726000 -12.115470 1
#> 2 1 -0.95 -2.35 0.5041335 -0.51810840 -0.4458665 -2.868108 1
#> 3 1 -6.20 -2.30 0.2347791 1.99681704 -5.9652209 -0.303183 2
#> 4 1 -13.90 -2.55 0.4909746 -0.08782500 -13.4090254 -2.637825 2
#> 5 1 -14.40 -5.80 -1.0817428 0.09356892 -15.4817428 -5.706431 2
#> 6 1 -3.60 -1.70 -0.1716076 0.47813314 -3.7716076 -1.221867 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -38100 7375
#> initial value 998.131940
#> iter 2 value 820.359070
#> iter 3 value 809.234542
#> iter 4 value 808.981016
#> iter 5 value 770.540398
#> iter 6 value 762.092484
#> iter 7 value 760.737481
#> iter 8 value 760.710046
#> iter 9 value 760.709998
#> iter 10 value 760.709983
#> iter 10 value 760.709974
#> iter 10 value 760.709966
#> final value 760.709966
#> converged
#> This is Run number 55
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.9081562 2.42970564 2.3581562 -10.170294 1
#> 2 1 -0.95 -2.35 0.3418053 -0.02434984 -0.6081947 -2.374350 1
#> 3 1 -6.20 -2.30 -0.5075199 -0.67135129 -6.7075199 -2.971351 2
#> 4 1 -13.90 -2.55 0.3120520 -0.21792546 -13.5879480 -2.767925 2
#> 5 1 -14.40 -5.80 0.2889016 0.88446951 -14.1110984 -4.915530 2
#> 6 1 -3.60 -1.70 0.3922307 0.33060741 -3.2077693 -1.369393 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5660 -36700 7575
#> initial value 998.131940
#> iter 2 value 838.829533
#> iter 3 value 826.877525
#> iter 4 value 825.526432
#> iter 5 value 783.392655
#> iter 6 value 775.339955
#> iter 7 value 774.050023
#> iter 8 value 774.027792
#> iter 9 value 774.027762
#> iter 9 value 774.027751
#> iter 9 value 774.027745
#> final value 774.027745
#> converged
#> This is Run number 56
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.002726308 -0.4310971 -0.5472737 -13.03109715 1
#> 2 1 -0.95 -2.35 0.029817228 0.1321433 -0.9201828 -2.21785665 1
#> 3 1 -6.20 -2.30 0.852524470 2.2600634 -5.3474755 -0.03993665 2
#> 4 1 -13.90 -2.55 -0.387014032 0.1709590 -14.2870140 -2.37904103 2
#> 5 1 -14.40 -5.80 -1.619565647 1.4339483 -16.0195656 -4.36605167 2
#> 6 1 -3.60 -1.70 -0.864710967 3.0335322 -4.4647110 1.33353222 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7200 -40600 6275
#> initial value 998.131940
#> iter 2 value 787.877907
#> iter 3 value 777.147900
#> iter 4 value 775.935444
#> iter 5 value 744.967575
#> iter 6 value 736.153199
#> iter 7 value 734.751407
#> iter 8 value 734.714794
#> iter 9 value 734.714716
#> iter 9 value 734.714705
#> iter 9 value 734.714697
#> final value 734.714697
#> converged
#> This is Run number 57
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9945020 0.520600487 0.444502 -12.079400 1
#> 2 1 -0.95 -2.35 -0.1858918 0.007004588 -1.135892 -2.342995 1
#> 3 1 -6.20 -2.30 -0.2102867 -0.641286324 -6.410287 -2.941286 2
#> 4 1 -13.90 -2.55 3.7337388 -0.089307883 -10.166261 -2.639308 2
#> 5 1 -14.40 -5.80 0.2335292 -0.627732068 -14.166471 -6.427732 2
#> 6 1 -3.60 -1.70 -0.3792656 1.148182025 -3.979266 -0.551818 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -40025 7000
#> initial value 998.131940
#> iter 2 value 793.717902
#> iter 3 value 780.617740
#> iter 4 value 779.324508
#> iter 5 value 746.808653
#> iter 6 value 738.088269
#> iter 7 value 736.817074
#> iter 8 value 736.788971
#> iter 9 value 736.788931
#> iter 9 value 736.788920
#> iter 9 value 736.788913
#> final value 736.788913
#> converged
#> This is Run number 58
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4571985 1.3058410927 -0.09280151 -11.294159 1
#> 2 1 -0.95 -2.35 -0.1937811 -1.0521658995 -1.14378108 -3.402166 1
#> 3 1 -6.20 -2.30 -0.9002293 -0.3171285445 -7.10022930 -2.617129 2
#> 4 1 -13.90 -2.55 2.0540424 -0.0008984213 -11.84595755 -2.550898 2
#> 5 1 -14.40 -5.80 1.2539520 0.2071496298 -13.14604797 -5.592850 2
#> 6 1 -3.60 -1.70 0.1663033 -0.2220928603 -3.43369670 -1.922093 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38425 6300
#> initial value 998.131940
#> iter 2 value 821.677556
#> iter 3 value 811.847539
#> iter 4 value 810.449793
#> iter 5 value 773.105717
#> iter 6 value 764.621464
#> iter 7 value 763.090220
#> iter 8 value 763.054354
#> iter 9 value 763.054274
#> iter 10 value 763.054262
#> iter 10 value 763.054255
#> iter 10 value 763.054252
#> final value 763.054252
#> converged
#> This is Run number 59
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.43597779 1.56527902 -0.9859778 -11.034721 1
#> 2 1 -0.95 -2.35 3.85699231 0.06030084 2.9069923 -2.289699 1
#> 3 1 -6.20 -2.30 0.28358072 0.33147899 -5.9164193 -1.968521 2
#> 4 1 -13.90 -2.55 -0.23075292 0.17126672 -14.1307529 -2.378733 2
#> 5 1 -14.40 -5.80 0.09154495 1.70106369 -14.3084551 -4.098936 2
#> 6 1 -3.60 -1.70 1.08872305 -0.50416569 -2.5112770 -2.204166 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38125 6675
#> initial value 998.131940
#> iter 2 value 824.153085
#> iter 3 value 813.691828
#> iter 4 value 812.473636
#> iter 5 value 774.255517
#> iter 6 value 765.832548
#> iter 7 value 764.377969
#> iter 8 value 764.345990
#> iter 9 value 764.345928
#> iter 9 value 764.345928
#> iter 9 value 764.345928
#> final value 764.345928
#> converged
#> This is Run number 60
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2508201 -0.3734890 -0.2991799 -12.973489 1
#> 2 1 -0.95 -2.35 -1.3414033 -0.5180348 -2.2914033 -2.868035 1
#> 3 1 -6.20 -2.30 4.8701170 0.1663493 -1.3298830 -2.133651 1
#> 4 1 -13.90 -2.55 2.8363642 2.9052270 -11.0636358 0.355227 2
#> 5 1 -14.40 -5.80 -0.1019067 1.4269929 -14.5019067 -4.373007 2
#> 6 1 -3.60 -1.70 -0.2679252 0.5507058 -3.8679252 -1.149294 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38625 6500
#> initial value 998.131940
#> iter 2 value 818.145445
#> iter 3 value 803.059787
#> iter 4 value 798.995026
#> iter 5 value 762.916691
#> iter 6 value 754.331446
#> iter 7 value 752.976540
#> iter 8 value 752.947464
#> iter 9 value 752.947416
#> iter 9 value 752.947407
#> iter 9 value 752.947403
#> final value 752.947403
#> converged
#> This is Run number 61
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.14092514 1.0831714 -0.6909251 -11.516829 1
#> 2 1 -0.95 -2.35 -0.08381742 -1.7439245 -1.0338174 -4.093924 1
#> 3 1 -6.20 -2.30 -0.42034058 0.8241373 -6.6203406 -1.475863 2
#> 4 1 -13.90 -2.55 3.81712748 -0.3536398 -10.0828725 -2.903640 2
#> 5 1 -14.40 -5.80 0.08110513 1.2564924 -14.3188949 -4.543508 2
#> 6 1 -3.60 -1.70 2.12373749 -0.3276367 -1.4762625 -2.027637 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38550 7450
#> initial value 998.131940
#> iter 2 value 813.862286
#> iter 3 value 800.098676
#> iter 4 value 798.591095
#> iter 5 value 761.819604
#> iter 6 value 753.332299
#> iter 7 value 752.054468
#> iter 8 value 752.029896
#> iter 9 value 752.029865
#> iter 9 value 752.029854
#> iter 9 value 752.029847
#> final value 752.029847
#> converged
#> This is Run number 62
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3758963 -0.43300879 -0.1741037 -13.0330088 1
#> 2 1 -0.95 -2.35 0.6072881 -0.06120956 -0.3427119 -2.4112096 1
#> 3 1 -6.20 -2.30 1.9644980 0.88644384 -4.2355020 -1.4135562 2
#> 4 1 -13.90 -2.55 -0.8964901 1.33120664 -14.7964901 -1.2187934 2
#> 5 1 -14.40 -5.80 -0.9474455 1.23384735 -15.3474455 -4.5661526 2
#> 6 1 -3.60 -1.70 -0.3889098 2.14841735 -3.9889098 0.4484173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -40725 6900
#> initial value 998.131940
#> iter 2 value 782.639395
#> iter 3 value 770.073151
#> iter 4 value 769.243252
#> iter 5 value 738.689303
#> iter 6 value 729.908723
#> iter 7 value 728.669815
#> iter 8 value 728.641377
#> iter 9 value 728.641335
#> iter 9 value 728.641324
#> iter 9 value 728.641316
#> final value 728.641316
#> converged
#> This is Run number 63
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.09708567 0.22972358 -0.4529143 -12.3702764 1
#> 2 1 -0.95 -2.35 -0.28340339 0.90102124 -1.2334034 -1.4489788 1
#> 3 1 -6.20 -2.30 -0.72245935 1.42273912 -6.9224594 -0.8772609 2
#> 4 1 -13.90 -2.55 -0.26040919 -0.55923959 -14.1604092 -3.1092396 2
#> 5 1 -14.40 -5.80 5.96485406 -0.04564194 -8.4351459 -5.8456419 2
#> 6 1 -3.60 -1.70 0.77720827 1.06356686 -2.8227917 -0.6364331 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37050 6825
#> initial value 998.131940
#> iter 2 value 838.484488
#> iter 3 value 826.128444
#> iter 4 value 823.520020
#> iter 5 value 782.698589
#> iter 6 value 774.543489
#> iter 7 value 773.173324
#> iter 8 value 773.147130
#> iter 9 value 773.147091
#> iter 9 value 773.147082
#> iter 9 value 773.147078
#> final value 773.147078
#> converged
#> This is Run number 64
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9645116 0.66883180 -1.5145116 -11.9311682 1
#> 2 1 -0.95 -2.35 1.3703464 0.50142487 0.4203464 -1.8485751 1
#> 3 1 -6.20 -2.30 2.4423214 -0.55877465 -3.7576786 -2.8587746 2
#> 4 1 -13.90 -2.55 0.9106932 -0.06069489 -12.9893068 -2.6106949 2
#> 5 1 -14.40 -5.80 0.7759955 5.06427833 -13.6240045 -0.7357217 2
#> 6 1 -3.60 -1.70 1.5890401 1.53529954 -2.0109599 -0.1647005 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38375 6575
#> initial value 998.131940
#> iter 2 value 821.095508
#> iter 3 value 810.427510
#> iter 4 value 808.992492
#> iter 5 value 771.547059
#> iter 6 value 763.067506
#> iter 7 value 761.604698
#> iter 8 value 761.571795
#> iter 9 value 761.571730
#> iter 9 value 761.571729
#> iter 9 value 761.571729
#> final value 761.571729
#> converged
#> This is Run number 65
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2704263 3.37310339 0.7204263 -9.226897 1
#> 2 1 -0.95 -2.35 -0.3886616 0.08641257 -1.3386616 -2.263587 1
#> 3 1 -6.20 -2.30 0.9599140 0.79382039 -5.2400860 -1.506180 2
#> 4 1 -13.90 -2.55 0.1436504 1.29666697 -13.7563496 -1.253333 2
#> 5 1 -14.40 -5.80 1.0584448 0.70018071 -13.3415552 -5.099819 2
#> 6 1 -3.60 -1.70 -0.9948526 3.43193013 -4.5948526 1.731930 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7500 -39325 5525
#> initial value 998.131940
#> iter 2 value 810.778554
#> iter 3 value 804.127351
#> iter 4 value 803.725034
#> iter 5 value 768.530008
#> iter 6 value 759.937831
#> iter 7 value 758.112106
#> iter 8 value 758.061529
#> iter 9 value 758.061358
#> iter 10 value 758.061342
#> iter 10 value 758.061342
#> iter 10 value 758.061336
#> final value 758.061336
#> converged
#> This is Run number 66
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.94274035 1.0587750 -1.492740 -11.5412250 1
#> 2 1 -0.95 -2.35 -0.50325596 0.5223148 -1.453256 -1.8276852 1
#> 3 1 -6.20 -2.30 0.85593397 1.1380797 -5.344066 -1.1619203 2
#> 4 1 -13.90 -2.55 0.90895125 0.5227077 -12.991049 -2.0272923 2
#> 5 1 -14.40 -5.80 0.05103792 1.1640035 -14.348962 -4.6359965 2
#> 6 1 -3.60 -1.70 -0.97035454 1.5549439 -4.570355 -0.1450561 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -40375 7175
#> initial value 998.131940
#> iter 2 value 787.535400
#> iter 3 value 771.277229
#> iter 4 value 768.428218
#> iter 5 value 737.516024
#> iter 6 value 728.858032
#> iter 7 value 727.703811
#> iter 8 value 727.680519
#> iter 9 value 727.680498
#> iter 9 value 727.680492
#> iter 9 value 727.680488
#> final value 727.680488
#> converged
#> This is Run number 67
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2173684 -0.3451926 1.667368 -12.945193 1
#> 2 1 -0.95 -2.35 -0.4137732 -0.3473576 -1.363773 -2.697358 1
#> 3 1 -6.20 -2.30 -1.0058077 0.3302565 -7.205808 -1.969743 2
#> 4 1 -13.90 -2.55 -0.2291413 -0.4238604 -14.129141 -2.973860 2
#> 5 1 -14.40 -5.80 -0.1175618 1.4433230 -14.517562 -4.356677 2
#> 6 1 -3.60 -1.70 2.3114642 0.6781493 -1.288536 -1.021851 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6300 -40450 6625
#> initial value 998.131940
#> iter 2 value 789.365128
#> iter 3 value 773.698035
#> iter 4 value 769.900117
#> iter 5 value 739.331998
#> iter 6 value 730.592069
#> iter 7 value 729.375716
#> iter 8 value 729.348246
#> iter 9 value 729.348207
#> iter 9 value 729.348202
#> iter 9 value 729.348197
#> final value 729.348197
#> converged
#> This is Run number 68
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9237850 0.3464801 1.373785 -12.253520 1
#> 2 1 -0.95 -2.35 2.1097690 0.8237414 1.159769 -1.526259 1
#> 3 1 -6.20 -2.30 0.6987535 0.4687134 -5.501246 -1.831287 2
#> 4 1 -13.90 -2.55 2.0057769 0.9240380 -11.894223 -1.625962 2
#> 5 1 -14.40 -5.80 -0.9823895 -0.8427107 -15.382389 -6.642711 2
#> 6 1 -3.60 -1.70 1.4806043 -0.5814357 -2.119396 -2.281436 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37975 7475
#> initial value 998.131940
#> iter 2 value 822.009027
#> iter 3 value 808.751339
#> iter 4 value 807.252887
#> iter 5 value 768.791592
#> iter 6 value 760.417338
#> iter 7 value 759.122939
#> iter 8 value 759.098674
#> iter 9 value 759.098642
#> iter 10 value 759.098630
#> iter 10 value 759.098621
#> iter 10 value 759.098615
#> final value 759.098615
#> converged
#> This is Run number 69
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2831594 -0.1999130 -0.2668406 -12.7999130 1
#> 2 1 -0.95 -2.35 0.4834013 -0.2763667 -0.4665987 -2.6263667 1
#> 3 1 -6.20 -2.30 1.1292655 1.5569049 -5.0707345 -0.7430951 2
#> 4 1 -13.90 -2.55 1.0461758 0.6917944 -12.8538242 -1.8582056 2
#> 5 1 -14.40 -5.80 1.4374732 -1.6730457 -12.9625268 -7.4730457 2
#> 6 1 -3.60 -1.70 1.0482825 4.2943994 -2.5517175 2.5943994 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7280 -40550 6250
#> initial value 998.131940
#> iter 2 value 788.693308
#> iter 3 value 778.388955
#> iter 4 value 777.399561
#> iter 5 value 746.195610
#> iter 6 value 737.380478
#> iter 7 value 735.951866
#> iter 8 value 735.914177
#> iter 9 value 735.914093
#> iter 10 value 735.914081
#> iter 10 value 735.914076
#> iter 10 value 735.914069
#> final value 735.914069
#> converged
#> This is Run number 70
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.98806493 1.14983111 2.4380649 -11.4501689 1
#> 2 1 -0.95 -2.35 1.31764356 0.70060328 0.3676436 -1.6493967 1
#> 3 1 -6.20 -2.30 0.27133930 2.84941387 -5.9286607 0.5494139 2
#> 4 1 -13.90 -2.55 -0.38386691 0.09670359 -14.2838669 -2.4532964 2
#> 5 1 -14.40 -5.80 -0.19966443 0.67225741 -14.5996644 -5.1277426 2
#> 6 1 -3.60 -1.70 0.05103394 0.68438236 -3.5489661 -1.0156176 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -40125 5975
#> initial value 998.131940
#> iter 2 value 796.656315
#> iter 3 value 787.797068
#> iter 4 value 787.032502
#> iter 5 value 754.410469
#> iter 6 value 745.639165
#> iter 7 value 744.060553
#> iter 8 value 744.017332
#> iter 9 value 744.017216
#> iter 10 value 744.017202
#> iter 10 value 744.017197
#> iter 10 value 744.017190
#> final value 744.017190
#> converged
#> This is Run number 71
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9558678 -0.28590425 1.40586777 -12.8859043 1
#> 2 1 -0.95 -2.35 0.9939595 -0.47121844 0.04395947 -2.8212184 1
#> 3 1 -6.20 -2.30 1.3622489 2.04312783 -4.83775108 -0.2568722 2
#> 4 1 -13.90 -2.55 0.8113508 6.91967651 -13.08864923 4.3696765 2
#> 5 1 -14.40 -5.80 1.3510047 0.06870411 -13.04899526 -5.7312959 2
#> 6 1 -3.60 -1.70 -2.0749149 -0.35809217 -5.67491489 -2.0580922 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -38800 7350
#> initial value 998.131940
#> iter 2 value 810.909720
#> iter 3 value 795.271293
#> iter 4 value 792.441926
#> iter 5 value 756.788568
#> iter 6 value 748.279850
#> iter 7 value 747.029721
#> iter 8 value 747.005883
#> iter 9 value 747.005858
#> iter 9 value 747.005849
#> iter 9 value 747.005844
#> final value 747.005844
#> converged
#> This is Run number 72
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.68005206 0.51367898 -1.230052 -12.086321 1
#> 2 1 -0.95 -2.35 3.89628108 -0.02885329 2.946281 -2.378853 1
#> 3 1 -6.20 -2.30 0.62907324 -1.11398545 -5.570927 -3.413985 2
#> 4 1 -13.90 -2.55 -1.17330829 -0.17502990 -15.073308 -2.725030 2
#> 5 1 -14.40 -5.80 1.83859271 -0.29812469 -12.561407 -6.098125 2
#> 6 1 -3.60 -1.70 -0.08773535 -0.55055796 -3.687735 -2.250558 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -38375 7200
#> initial value 998.131940
#> iter 2 value 817.996336
#> iter 3 value 802.495944
#> iter 4 value 799.232143
#> iter 5 value 762.401709
#> iter 6 value 753.947707
#> iter 7 value 752.666703
#> iter 8 value 752.642195
#> iter 9 value 752.642168
#> iter 9 value 752.642159
#> iter 9 value 752.642155
#> final value 752.642155
#> converged
#> This is Run number 73
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.0637934 0.8624431 0.5137934 -11.7375569 1
#> 2 1 -0.95 -2.35 0.6601374 -0.7218626 -0.2898626 -3.0718626 1
#> 3 1 -6.20 -2.30 -0.8427415 0.5771343 -7.0427415 -1.7228657 2
#> 4 1 -13.90 -2.55 1.6078021 0.4439846 -12.2921979 -2.1060154 2
#> 5 1 -14.40 -5.80 0.1739378 -0.2364939 -14.2260622 -6.0364939 2
#> 6 1 -3.60 -1.70 1.1675201 1.0402617 -2.4324799 -0.6597383 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6780 -38900 6825
#> initial value 998.131940
#> iter 2 value 811.772035
#> iter 3 value 801.083775
#> iter 4 value 800.422025
#> iter 5 value 764.297307
#> iter 6 value 755.700620
#> iter 7 value 754.275055
#> iter 8 value 754.242478
#> iter 9 value 754.242413
#> iter 10 value 754.242398
#> iter 10 value 754.242388
#> iter 10 value 754.242381
#> final value 754.242381
#> converged
#> This is Run number 74
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.2924840 0.8739020 1.7424840 -11.726098 1
#> 2 1 -0.95 -2.35 0.1284661 -0.1764717 -0.8215339 -2.526472 1
#> 3 1 -6.20 -2.30 1.0086759 0.4222885 -5.1913241 -1.877712 2
#> 4 1 -13.90 -2.55 2.2127638 0.3745331 -11.6872362 -2.175467 2
#> 5 1 -14.40 -5.80 -0.2433684 4.5157374 -14.6433684 -1.284263 2
#> 6 1 -3.60 -1.70 1.1963571 -0.6265572 -2.4036429 -2.326557 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -40325 5425
#> initial value 998.131940
#> iter 2 value 796.625937
#> iter 3 value 785.810638
#> iter 4 value 782.689526
#> iter 5 value 751.417583
#> iter 6 value 742.606890
#> iter 7 value 741.008584
#> iter 8 value 740.961345
#> iter 9 value 740.961168
#> iter 10 value 740.961150
#> iter 10 value 740.961150
#> iter 11 value 740.961138
#> iter 11 value 740.961135
#> iter 11 value 740.961133
#> final value 740.961133
#> converged
#> This is Run number 75
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7526788 0.7104879 -1.3026788 -11.889512 1
#> 2 1 -0.95 -2.35 1.0967658 1.1902048 0.1467658 -1.159795 1
#> 3 1 -6.20 -2.30 1.2696449 -0.8296046 -4.9303551 -3.129605 2
#> 4 1 -13.90 -2.55 0.4102497 2.8696700 -13.4897503 0.319670 2
#> 5 1 -14.40 -5.80 0.9725670 0.9143179 -13.4274330 -4.885682 2
#> 6 1 -3.60 -1.70 1.5803217 -0.8893010 -2.0196783 -2.589301 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -39500 7300
#> initial value 998.131940
#> iter 2 value 800.275257
#> iter 3 value 786.800005
#> iter 4 value 785.724964
#> iter 5 value 751.632452
#> iter 6 value 742.982749
#> iter 7 value 741.721943
#> iter 8 value 741.695990
#> iter 9 value 741.695955
#> iter 10 value 741.695944
#> iter 10 value 741.695935
#> iter 10 value 741.695928
#> final value 741.695928
#> converged
#> This is Run number 76
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.002203018 1.84932479 -0.5522030 -10.750675 1
#> 2 1 -0.95 -2.35 0.055219473 0.35429777 -0.8947805 -1.995702 1
#> 3 1 -6.20 -2.30 -0.688342460 -0.02749961 -6.8883425 -2.327500 2
#> 4 1 -13.90 -2.55 1.096123941 0.52721483 -12.8038761 -2.022785 2
#> 5 1 -14.40 -5.80 0.887343077 1.54773004 -13.5126569 -4.252270 2
#> 6 1 -3.60 -1.70 0.093306994 0.19990133 -3.5066930 -1.500099 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7380 -39075 6425
#> initial value 998.131940
#> iter 2 value 810.468861
#> iter 3 value 801.910484
#> iter 4 value 801.830183
#> iter 5 value 765.949678
#> iter 6 value 757.354382
#> iter 7 value 755.771362
#> iter 8 value 755.731368
#> iter 9 value 755.731260
#> iter 10 value 755.731242
#> iter 10 value 755.731234
#> iter 10 value 755.731226
#> final value 755.731226
#> converged
#> This is Run number 77
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1461190 -0.1267509 -0.696119 -12.7267509 1
#> 2 1 -0.95 -2.35 -0.1065639 1.4266081 -1.056564 -0.9233919 2
#> 3 1 -6.20 -2.30 0.8214025 -0.2072795 -5.378598 -2.5072795 2
#> 4 1 -13.90 -2.55 -1.3949348 -1.2271316 -15.294935 -3.7771316 2
#> 5 1 -14.40 -5.80 1.0483308 0.9607808 -13.351669 -4.8392192 2
#> 6 1 -3.60 -1.70 1.4301829 0.2960541 -2.169817 -1.4039459 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -38075 7150
#> initial value 998.131940
#> iter 2 value 822.471399
#> iter 3 value 809.775560
#> iter 4 value 808.022519
#> iter 5 value 769.885747
#> iter 6 value 761.481827
#> iter 7 value 760.141959
#> iter 8 value 760.115221
#> iter 9 value 760.115181
#> iter 10 value 760.115169
#> iter 10 value 760.115160
#> iter 10 value 760.115160
#> final value 760.115160
#> converged
#> This is Run number 78
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8893032 1.9656623 -1.43930316 -10.634338 1
#> 2 1 -0.95 -2.35 3.3472836 0.4352147 2.39728364 -1.914785 1
#> 3 1 -6.20 -2.30 -0.4710426 -0.6388205 -6.67104263 -2.938821 2
#> 4 1 -13.90 -2.55 0.6830566 -0.3580751 -13.21694344 -2.908075 2
#> 5 1 -14.40 -5.80 -0.1114782 1.2884228 -14.51147819 -4.511577 2
#> 6 1 -3.60 -1.70 3.5861732 0.1459608 -0.01382677 -1.554039 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -40625 6975
#> initial value 998.131940
#> iter 2 value 784.520677
#> iter 3 value 769.116361
#> iter 4 value 766.435370
#> iter 5 value 736.184360
#> iter 6 value 727.483128
#> iter 7 value 726.315096
#> iter 8 value 726.290190
#> iter 9 value 726.290163
#> iter 9 value 726.290163
#> iter 9 value 726.290163
#> final value 726.290163
#> converged
#> This is Run number 79
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1567705 -0.1169315 -0.7067705 -12.7169315 1
#> 2 1 -0.95 -2.35 1.3874137 0.1202300 0.4374137 -2.2297700 1
#> 3 1 -6.20 -2.30 1.0389011 4.0860144 -5.1610989 1.7860144 2
#> 4 1 -13.90 -2.55 0.9800581 -1.1122798 -12.9199419 -3.6622798 2
#> 5 1 -14.40 -5.80 2.8822508 1.6856565 -11.5177492 -4.1143435 2
#> 6 1 -3.60 -1.70 -0.4873458 2.0758497 -4.0873458 0.3758497 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -39675 6425
#> initial value 998.131940
#> iter 2 value 802.589947
#> iter 3 value 788.890342
#> iter 4 value 785.685694
#> iter 5 value 752.574239
#> iter 6 value 743.859365
#> iter 7 value 742.502476
#> iter 8 value 742.470541
#> iter 9 value 742.470483
#> iter 9 value 742.470475
#> iter 9 value 742.470469
#> final value 742.470469
#> converged
#> This is Run number 80
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6986578 0.84202093 1.148658 -11.757979 1
#> 2 1 -0.95 -2.35 0.6242290 -0.78962108 -0.325771 -3.139621 1
#> 3 1 -6.20 -2.30 0.4635686 1.13209145 -5.736431 -1.167909 2
#> 4 1 -13.90 -2.55 -0.5302197 0.16731670 -14.430220 -2.382683 2
#> 5 1 -14.40 -5.80 1.3253005 1.37522472 -13.074700 -4.424775 2
#> 6 1 -3.60 -1.70 0.4165892 0.03988974 -3.183411 -1.660110 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -41325 6975
#> initial value 998.131940
#> iter 2 value 773.106087
#> iter 3 value 755.069418
#> iter 4 value 750.865562
#> iter 5 value 723.186784
#> iter 6 value 714.574958
#> iter 7 value 713.534303
#> iter 8 value 713.513225
#> iter 9 value 713.513212
#> iter 9 value 713.513209
#> iter 9 value 713.513206
#> final value 713.513206
#> converged
#> This is Run number 81
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8857455 0.69194360 2.335746 -11.908056 1
#> 2 1 -0.95 -2.35 -0.4785646 0.15365553 -1.428565 -2.196344 1
#> 3 1 -6.20 -2.30 0.6992334 0.85319884 -5.500767 -1.446801 2
#> 4 1 -13.90 -2.55 0.5870290 0.08244343 -13.312971 -2.467557 2
#> 5 1 -14.40 -5.80 -1.5699970 1.28708053 -15.969997 -4.512919 2
#> 6 1 -3.60 -1.70 -0.4917272 -0.33048189 -4.091727 -2.030482 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -39275 7600
#> initial value 998.131940
#> iter 2 value 802.288107
#> iter 3 value 785.872757
#> iter 4 value 783.411391
#> iter 5 value 749.140416
#> iter 6 value 740.601795
#> iter 7 value 739.410538
#> iter 8 value 739.388807
#> iter 9 value 739.388788
#> iter 9 value 739.388781
#> iter 9 value 739.388780
#> final value 739.388780
#> converged
#> This is Run number 82
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6815306 -0.4990454 0.1315306 -13.09904539 1
#> 2 1 -0.95 -2.35 -0.2967441 2.4164207 -1.2467441 0.06642072 2
#> 3 1 -6.20 -2.30 0.1689444 0.7661130 -6.0310556 -1.53388699 2
#> 4 1 -13.90 -2.55 0.4964737 1.8496352 -13.4035263 -0.70036480 2
#> 5 1 -14.40 -5.80 0.8407347 1.0421646 -13.5592653 -4.75783541 2
#> 6 1 -3.60 -1.70 -1.2571612 1.8605432 -4.8571612 0.16054320 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -39150 6800
#> initial value 998.131940
#> iter 2 value 808.056514
#> iter 3 value 797.396430
#> iter 4 value 796.824326
#> iter 5 value 761.404299
#> iter 6 value 752.761342
#> iter 7 value 751.337283
#> iter 8 value 751.304138
#> iter 9 value 751.304071
#> iter 10 value 751.304056
#> iter 10 value 751.304046
#> iter 10 value 751.304039
#> final value 751.304039
#> converged
#> This is Run number 83
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5597245 -1.0562157 -1.109724 -13.6562157 1
#> 2 1 -0.95 -2.35 2.2426874 1.4630482 1.292687 -0.8869518 1
#> 3 1 -6.20 -2.30 -0.1302133 1.6207747 -6.330213 -0.6792253 2
#> 4 1 -13.90 -2.55 2.7377421 0.7494584 -11.162258 -1.8005416 2
#> 5 1 -14.40 -5.80 -0.6496455 -0.6952994 -15.049646 -6.4952994 2
#> 6 1 -3.60 -1.70 -0.4470218 0.6057720 -4.047022 -1.0942280 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38400 7275
#> initial value 998.131940
#> iter 2 value 816.973242
#> iter 3 value 804.458518
#> iter 4 value 803.292750
#> iter 5 value 765.943703
#> iter 6 value 757.464569
#> iter 7 value 756.138870
#> iter 8 value 756.112181
#> iter 9 value 756.112140
#> iter 10 value 756.112128
#> iter 10 value 756.112118
#> iter 10 value 756.112112
#> final value 756.112112
#> converged
#> This is Run number 84
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.00565409 1.4715000 -0.5556541 -11.1285000 1
#> 2 1 -0.95 -2.35 -0.86209904 -0.8104365 -1.8120990 -3.1604365 1
#> 3 1 -6.20 -2.30 -1.23565575 0.4038228 -7.4356557 -1.8961772 2
#> 4 1 -13.90 -2.55 -0.13403324 4.4855720 -14.0340332 1.9355720 2
#> 5 1 -14.40 -5.80 0.02812253 2.0297037 -14.3718775 -3.7702963 2
#> 6 1 -3.60 -1.70 -0.09737891 2.2596579 -3.6973789 0.5596579 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39675 6475
#> initial value 998.131940
#> iter 2 value 802.092574
#> iter 3 value 790.123337
#> iter 4 value 788.155126
#> iter 5 value 754.686635
#> iter 6 value 745.975887
#> iter 7 value 744.577068
#> iter 8 value 744.543447
#> iter 9 value 744.543383
#> iter 9 value 744.543373
#> iter 9 value 744.543366
#> final value 744.543366
#> converged
#> This is Run number 85
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.23782935 1.22338909 -0.7878293 -11.3766109 1
#> 2 1 -0.95 -2.35 -0.89027730 0.14954986 -1.8402773 -2.2004501 1
#> 3 1 -6.20 -2.30 0.01225359 2.07308943 -6.1877464 -0.2269106 2
#> 4 1 -13.90 -2.55 -0.56036504 -0.07918101 -14.4603650 -2.6291810 2
#> 5 1 -14.40 -5.80 -0.50471200 -1.03424789 -14.9047120 -6.8342479 2
#> 6 1 -3.60 -1.70 1.39182076 4.74249936 -2.2081792 3.0424994 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -39125 5950
#> initial value 998.131940
#> iter 2 value 813.102193
#> iter 3 value 802.363339
#> iter 4 value 799.959552
#> iter 5 value 764.939601
#> iter 6 value 756.303575
#> iter 7 value 754.747740
#> iter 8 value 754.708418
#> iter 9 value 754.708319
#> iter 10 value 754.708306
#> iter 10 value 754.708306
#> iter 10 value 754.708301
#> final value 754.708301
#> converged
#> This is Run number 86
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.71164782 -0.0003000682 -1.2616478 -12.600300 1
#> 2 1 -0.95 -2.35 0.02092574 1.2677891730 -0.9290743 -1.082211 1
#> 3 1 -6.20 -2.30 0.07405645 -0.9306325511 -6.1259435 -3.230633 2
#> 4 1 -13.90 -2.55 -0.46904329 0.5459137931 -14.3690433 -2.004086 2
#> 5 1 -14.40 -5.80 0.26722338 -0.1514355147 -14.1327766 -5.951436 2
#> 6 1 -3.60 -1.70 -0.10558449 0.0898571504 -3.7055845 -1.610143 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -37025 8075
#> initial value 998.131940
#> iter 2 value 831.429429
#> iter 3 value 817.182107
#> iter 4 value 815.542847
#> iter 5 value 774.386792
#> iter 6 value 766.259396
#> iter 7 value 765.033427
#> iter 8 value 765.014414
#> iter 8 value 765.014405
#> final value 765.014405
#> converged
#> This is Run number 87
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7188451 0.2618778 -1.268845 -12.3381222 1
#> 2 1 -0.95 -2.35 2.2075609 1.6493675 1.257561 -0.7006325 1
#> 3 1 -6.20 -2.30 -0.8432090 2.0008099 -7.043209 -0.2991901 2
#> 4 1 -13.90 -2.55 -0.6457151 0.1147588 -14.545715 -2.4352412 2
#> 5 1 -14.40 -5.80 0.9222172 3.6196986 -13.477783 -2.1803014 2
#> 6 1 -3.60 -1.70 -1.2049979 -0.9766591 -4.804998 -2.6766591 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -39850 7650
#> initial value 998.131940
#> iter 2 value 793.110813
#> iter 3 value 775.933356
#> iter 4 value 773.456835
#> iter 5 value 740.961570
#> iter 6 value 732.397012
#> iter 7 value 731.258090
#> iter 8 value 731.237662
#> iter 8 value 731.237660
#> final value 731.237660
#> converged
#> This is Run number 88
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.744638159 1.03020721 1.194638 -11.569793 1
#> 2 1 -0.95 -2.35 -0.793194933 -1.07851091 -1.743195 -3.428511 1
#> 3 1 -6.20 -2.30 -0.007010485 0.61980791 -6.207010 -1.680192 2
#> 4 1 -13.90 -2.55 1.177290376 0.86976812 -12.722710 -1.680232 2
#> 5 1 -14.40 -5.80 -1.132210133 0.72612006 -15.532210 -5.073880 2
#> 6 1 -3.60 -1.70 -0.072517801 -0.06271019 -3.672518 -1.762710 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -38175 6300
#> initial value 998.131940
#> iter 2 value 825.198873
#> iter 3 value 816.019724
#> iter 4 value 814.950279
#> iter 5 value 776.785208
#> iter 6 value 768.364234
#> iter 7 value 766.812165
#> iter 8 value 766.776137
#> iter 9 value 766.776054
#> iter 9 value 766.776054
#> iter 9 value 766.776054
#> final value 766.776054
#> converged
#> This is Run number 89
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4232817 2.07696403 0.8732817 -10.523036 1
#> 2 1 -0.95 -2.35 2.7080865 0.94286474 1.7580865 -1.407135 1
#> 3 1 -6.20 -2.30 3.0254708 0.89297547 -3.1745292 -1.407025 2
#> 4 1 -13.90 -2.55 -1.0799164 0.61342594 -14.9799164 -1.936574 2
#> 5 1 -14.40 -5.80 0.8685468 0.70204311 -13.5314532 -5.097957 2
#> 6 1 -3.60 -1.70 -0.2552806 -0.03218343 -3.8552806 -1.732183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -39800 6050
#> initial value 998.131940
#> iter 2 value 802.352330
#> iter 3 value 790.135954
#> iter 4 value 787.157110
#> iter 5 value 754.310293
#> iter 6 value 745.562416
#> iter 7 value 744.107272
#> iter 8 value 744.070061
#> iter 9 value 744.069972
#> iter 9 value 744.069962
#> iter 9 value 744.069955
#> final value 744.069955
#> converged
#> This is Run number 90
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.44094030 -0.32883801 -0.9909403 -12.928838 1
#> 2 1 -0.95 -2.35 0.87180930 0.39872858 -0.0781907 -1.951271 1
#> 3 1 -6.20 -2.30 0.53070026 -0.31913791 -5.6692997 -2.619138 2
#> 4 1 -13.90 -2.55 1.50135707 -0.31045543 -12.3986429 -2.860455 2
#> 5 1 -14.40 -5.80 -0.06862105 -0.07179713 -14.4686210 -5.871797 2
#> 6 1 -3.60 -1.70 0.23052304 5.12983842 -3.3694770 3.429838 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -37325 7500
#> initial value 998.131940
#> iter 2 value 830.755377
#> iter 3 value 819.355764
#> iter 4 value 818.675097
#> iter 5 value 778.120094
#> iter 6 value 769.875666
#> iter 7 value 768.553430
#> iter 8 value 768.528831
#> iter 9 value 768.528793
#> iter 10 value 768.528780
#> iter 10 value 768.528771
#> iter 10 value 768.528764
#> final value 768.528764
#> converged
#> This is Run number 91
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8172137 2.77756144 0.2672137 -9.8224386 1
#> 2 1 -0.95 -2.35 4.8469756 0.09810341 3.8969756 -2.2518966 1
#> 3 1 -6.20 -2.30 0.4007139 0.84027400 -5.7992861 -1.4597260 2
#> 4 1 -13.90 -2.55 -0.1725408 1.84094520 -14.0725408 -0.7090548 2
#> 5 1 -14.40 -5.80 0.8811397 2.08972692 -13.5188603 -3.7102731 2
#> 6 1 -3.60 -1.70 0.1976318 -1.13201925 -3.4023682 -2.8320192 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -37850 6275
#> initial value 998.131940
#> iter 2 value 830.048550
#> iter 3 value 820.774742
#> iter 4 value 819.462971
#> iter 5 value 780.467786
#> iter 6 value 772.128770
#> iter 7 value 770.585173
#> iter 8 value 770.550348
#> iter 9 value 770.550270
#> iter 9 value 770.550270
#> iter 9 value 770.550270
#> final value 770.550270
#> converged
#> This is Run number 92
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3782552 0.5277570 -0.9282552 -12.0722430 1
#> 2 1 -0.95 -2.35 0.3848940 1.7450431 -0.5651060 -0.6049569 1
#> 3 1 -6.20 -2.30 1.2760597 0.1427823 -4.9239403 -2.1572177 2
#> 4 1 -13.90 -2.55 0.2774260 -0.8705159 -13.6225740 -3.4205159 2
#> 5 1 -14.40 -5.80 -0.6837159 0.7658291 -15.0837159 -5.0341709 2
#> 6 1 -3.60 -1.70 -0.5557368 1.8227113 -4.1557368 0.1227113 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -40900 8025
#> initial value 998.131940
#> iter 2 value 773.525140
#> iter 3 value 755.780727
#> iter 4 value 754.784495
#> iter 5 value 725.218662
#> iter 6 value 716.705448
#> iter 7 value 715.693984
#> iter 8 value 715.678378
#> iter 9 value 715.678363
#> iter 9 value 715.678358
#> iter 9 value 715.678358
#> final value 715.678358
#> converged
#> This is Run number 93
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.42406469 -0.45506422 -0.1259353 -13.0550642 1
#> 2 1 -0.95 -2.35 0.26999715 1.10979980 -0.6800028 -1.2402002 1
#> 3 1 -6.20 -2.30 -0.53698555 -1.93636105 -6.7369856 -4.2363611 2
#> 4 1 -13.90 -2.55 0.42871830 0.02752338 -13.4712817 -2.5224766 2
#> 5 1 -14.40 -5.80 0.02837421 0.17888129 -14.3716258 -5.6211187 2
#> 6 1 -3.60 -1.70 3.16162656 0.87174521 -0.4383734 -0.8282548 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -40575 5175
#> initial value 998.131940
#> iter 2 value 793.018991
#> iter 3 value 784.664339
#> iter 4 value 782.695933
#> iter 5 value 751.848644
#> iter 6 value 743.072806
#> iter 7 value 741.320183
#> iter 8 value 741.265254
#> iter 9 value 741.265030
#> iter 10 value 741.265009
#> iter 10 value 741.265009
#> iter 11 value 741.264996
#> iter 11 value 741.264993
#> iter 11 value 741.264990
#> final value 741.264990
#> converged
#> This is Run number 94
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7860526 0.2175871 0.2360526 -12.382413 1
#> 2 1 -0.95 -2.35 1.4269285 -0.3319648 0.4769285 -2.681965 1
#> 3 1 -6.20 -2.30 1.6028516 -0.7671012 -4.5971484 -3.067101 2
#> 4 1 -13.90 -2.55 -0.5500101 -0.6169612 -14.4500101 -3.166961 2
#> 5 1 -14.40 -5.80 0.6854648 -0.7490042 -13.7145352 -6.549004 2
#> 6 1 -3.60 -1.70 -1.0744341 0.6171008 -4.6744341 -1.082899 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -37875 6500
#> initial value 998.131940
#> iter 2 value 827.873844
#> iter 3 value 819.910406
#> iter 4 value 819.823583
#> iter 5 value 780.536525
#> iter 6 value 772.212288
#> iter 7 value 770.626266
#> iter 8 value 770.589427
#> iter 9 value 770.589330
#> iter 10 value 770.589313
#> iter 10 value 770.589304
#> iter 10 value 770.589297
#> final value 770.589297
#> converged
#> This is Run number 95
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.52030281 -1.0448761 -1.0703028 -13.644876 1
#> 2 1 -0.95 -2.35 0.50106016 0.1937960 -0.4489398 -2.156204 1
#> 3 1 -6.20 -2.30 1.13885214 5.1724104 -5.0611479 2.872410 2
#> 4 1 -13.90 -2.55 0.07858258 0.4218970 -13.8214174 -2.128103 2
#> 5 1 -14.40 -5.80 2.27074668 -0.1716853 -12.1292533 -5.971685 2
#> 6 1 -3.60 -1.70 -1.19075772 -0.2243023 -4.7907577 -1.924302 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -37925 6300
#> initial value 998.131940
#> iter 2 value 829.153988
#> iter 3 value 816.959339
#> iter 4 value 813.984339
#> iter 5 value 775.667894
#> iter 6 value 767.263657
#> iter 7 value 765.802217
#> iter 8 value 765.770403
#> iter 9 value 765.770341
#> iter 9 value 765.770331
#> iter 9 value 765.770326
#> final value 765.770326
#> converged
#> This is Run number 96
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4619269 0.1830388 -0.08807309 -12.416961 1
#> 2 1 -0.95 -2.35 -1.1055677 1.2947104 -2.05556768 -1.055290 2
#> 3 1 -6.20 -2.30 -0.9920002 0.7381641 -7.19200015 -1.561836 2
#> 4 1 -13.90 -2.55 1.2400074 -1.8832944 -12.65999258 -4.433294 2
#> 5 1 -14.40 -5.80 -0.8096838 1.3550804 -15.20968378 -4.444920 2
#> 6 1 -3.60 -1.70 1.3494219 4.5936374 -2.25057807 2.893637 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -36625 7350
#> initial value 998.131940
#> iter 2 value 841.160825
#> iter 3 value 829.191831
#> iter 4 value 827.394110
#> iter 5 value 785.186479
#> iter 6 value 777.164053
#> iter 7 value 775.854991
#> iter 8 value 775.831950
#> iter 9 value 775.831919
#> iter 9 value 775.831908
#> iter 9 value 775.831903
#> final value 775.831903
#> converged
#> This is Run number 97
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.001834528 0.1211372 -0.5481655 -12.47886279 1
#> 2 1 -0.95 -2.35 -0.364888939 1.0070213 -1.3148889 -1.34297872 1
#> 3 1 -6.20 -2.30 -1.023418534 2.2813831 -7.2234185 -0.01861692 2
#> 4 1 -13.90 -2.55 0.084338947 -0.5288091 -13.8156611 -3.07880910 2
#> 5 1 -14.40 -5.80 1.765133967 -1.6300936 -12.6348660 -7.43009358 2
#> 6 1 -3.60 -1.70 0.401290546 1.9348229 -3.1987095 0.23482287 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37975 6400
#> initial value 998.131940
#> iter 2 value 827.830640
#> iter 3 value 817.119439
#> iter 4 value 815.163047
#> iter 5 value 776.729990
#> iter 6 value 768.343618
#> iter 7 value 766.859410
#> iter 8 value 766.826619
#> iter 9 value 766.826554
#> iter 9 value 766.826543
#> iter 9 value 766.826537
#> final value 766.826537
#> converged
#> This is Run number 98
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2214239 0.23385145 -0.7714239 -12.3661486 1
#> 2 1 -0.95 -2.35 0.1485121 2.05537818 -0.8014879 -0.2946218 2
#> 3 1 -6.20 -2.30 -0.5975881 -0.08669776 -6.7975881 -2.3866978 2
#> 4 1 -13.90 -2.55 -0.5028826 0.77572753 -14.4028826 -1.7742725 2
#> 5 1 -14.40 -5.80 -1.0752891 -0.56008177 -15.4752891 -6.3600818 2
#> 6 1 -3.60 -1.70 1.7581633 -0.53301247 -1.8418367 -2.2330125 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39125 7225
#> initial value 998.131940
#> iter 2 value 806.211272
#> iter 3 value 794.130963
#> iter 4 value 793.577324
#> iter 5 value 758.186887
#> iter 6 value 749.557951
#> iter 7 value 748.233117
#> iter 8 value 748.204899
#> iter 9 value 748.204853
#> iter 10 value 748.204839
#> iter 10 value 748.204830
#> iter 10 value 748.204822
#> final value 748.204822
#> converged
#> This is Run number 99
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.06519970 0.2946808 0.5151997 -12.3053192 1
#> 2 1 -0.95 -2.35 0.36221651 0.2169767 -0.5877835 -2.1330233 1
#> 3 1 -6.20 -2.30 -0.15168121 2.4710551 -6.3516812 0.1710551 2
#> 4 1 -13.90 -2.55 2.97693647 1.4339706 -10.9230635 -1.1160294 2
#> 5 1 -14.40 -5.80 0.00316157 0.9153798 -14.3968384 -4.8846202 2
#> 6 1 -3.60 -1.70 1.30588506 1.3028120 -2.2941149 -0.3971880 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37725 7425
#> initial value 998.131940
#> iter 2 value 825.897094
#> iter 3 value 811.151912
#> iter 4 value 808.437890
#> iter 5 value 769.592293
#> iter 6 value 761.286919
#> iter 7 value 760.005446
#> iter 8 value 759.982305
#> iter 9 value 759.982279
#> iter 9 value 759.982270
#> iter 9 value 759.982265
#> final value 759.982265
#> converged
#> This is Run number 100
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5424929 0.8393994 -0.007507102 -11.760601 1
#> 2 1 -0.95 -2.35 1.3364321 -0.5358660 0.386432058 -2.885866 1
#> 3 1 -6.20 -2.30 3.2140910 -0.3558320 -2.985909045 -2.655832 2
#> 4 1 -13.90 -2.55 -1.1102428 1.6823350 -15.010242773 -0.867665 2
#> 5 1 -14.40 -5.80 -0.8430685 1.5801660 -15.243068486 -4.219834 2
#> 6 1 -3.60 -1.70 -0.3074278 0.3142555 -3.907427819 -1.385744 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -37450 6825
#> initial value 998.131940
#> iter 2 value 833.021894
#> iter 3 value 821.415000
#> iter 4 value 819.414169
#> iter 5 value 779.545122
#> iter 6 value 771.290314
#> iter 7 value 769.895365
#> iter 8 value 769.867357
#> iter 9 value 769.867311
#> iter 9 value 769.867300
#> iter 9 value 769.867295
#> final value 769.867295
#> converged
#> This is Run number 101
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4177567 1.1234849 -0.9677567 -11.476515 1
#> 2 1 -0.95 -2.35 -0.8108214 0.2932045 -1.7608214 -2.056796 1
#> 3 1 -6.20 -2.30 -0.7437990 1.1748935 -6.9437990 -1.125107 2
#> 4 1 -13.90 -2.55 -0.2841491 -0.5240037 -14.1841491 -3.074004 2
#> 5 1 -14.40 -5.80 2.0962448 1.6465735 -12.3037552 -4.153427 2
#> 6 1 -3.60 -1.70 0.5646285 0.9756100 -3.0353715 -0.724390 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -40125 7000
#> initial value 998.131940
#> iter 2 value 792.574507
#> iter 3 value 776.314691
#> iter 4 value 772.897455
#> iter 5 value 741.332557
#> iter 6 value 732.660217
#> iter 7 value 731.467736
#> iter 8 value 731.442932
#> iter 9 value 731.442906
#> iter 9 value 731.442900
#> iter 9 value 731.442896
#> final value 731.442896
#> converged
#> This is Run number 102
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1628389 -1.1173058 -0.3871611 -13.717306 1
#> 2 1 -0.95 -2.35 0.4535009 1.3115566 -0.4964991 -1.038443 1
#> 3 1 -6.20 -2.30 1.8628134 -0.1766261 -4.3371866 -2.476626 2
#> 4 1 -13.90 -2.55 -0.3649576 0.4817129 -14.2649576 -2.068287 2
#> 5 1 -14.40 -5.80 2.8226493 -0.7196365 -11.5773507 -6.519637 2
#> 6 1 -3.60 -1.70 0.9927357 0.1253296 -2.6072643 -1.574670 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5440 -37450 8125
#> initial value 998.131940
#> iter 2 value 825.356584
#> iter 3 value 809.639500
#> iter 4 value 807.503829
#> iter 5 value 767.735343
#> iter 6 value 759.529343
#> iter 7 value 758.317293
#> iter 8 value 758.298615
#> iter 9 value 758.298600
#> iter 9 value 758.298598
#> iter 10 value 758.298587
#> iter 10 value 758.298579
#> iter 10 value 758.298579
#> final value 758.298579
#> converged
#> This is Run number 103
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.07796849 1.3753498 -0.4720315 -11.224650 1
#> 2 1 -0.95 -2.35 -0.06360688 0.9425686 -1.0136069 -1.407431 1
#> 3 1 -6.20 -2.30 0.08685488 -0.6554985 -6.1131451 -2.955499 2
#> 4 1 -13.90 -2.55 -0.66296248 1.3728537 -14.5629625 -1.177146 2
#> 5 1 -14.40 -5.80 1.67964597 2.4150648 -12.7203540 -3.384935 2
#> 6 1 -3.60 -1.70 0.09866260 0.5150201 -3.5013374 -1.184980 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7180 -40400 6400
#> initial value 998.131940
#> iter 2 value 790.484082
#> iter 3 value 779.725808
#> iter 4 value 778.723689
#> iter 5 value 747.099805
#> iter 6 value 738.300139
#> iter 7 value 736.900041
#> iter 8 value 736.864265
#> iter 9 value 736.864191
#> iter 10 value 736.864179
#> iter 10 value 736.864173
#> iter 10 value 736.864166
#> final value 736.864166
#> converged
#> This is Run number 104
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.5828111 -0.53231778 1.032811 -13.132318 1
#> 2 1 -0.95 -2.35 -0.2370028 0.52920908 -1.187003 -1.820791 1
#> 3 1 -6.20 -2.30 0.5973776 3.61496297 -5.602622 1.314963 2
#> 4 1 -13.90 -2.55 -0.1884095 -0.31090653 -14.088409 -2.860907 2
#> 5 1 -14.40 -5.80 1.1612007 -0.06128768 -13.238799 -5.861288 2
#> 6 1 -3.60 -1.70 0.6454892 -0.80832087 -2.954511 -2.508321 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -38275 7525
#> initial value 998.131940
#> iter 2 value 817.536131
#> iter 3 value 801.675184
#> iter 4 value 798.781680
#> iter 5 value 761.613672
#> iter 6 value 753.209023
#> iter 7 value 751.960521
#> iter 8 value 751.938043
#> iter 9 value 751.938021
#> iter 9 value 751.938013
#> iter 9 value 751.938008
#> final value 751.938008
#> converged
#> This is Run number 105
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.40524442 -0.5430965 0.8552444 -13.143097 1
#> 2 1 -0.95 -2.35 0.06301837 -0.4978175 -0.8869816 -2.847817 1
#> 3 1 -6.20 -2.30 -0.27339252 -0.8589458 -6.4733925 -3.158946 2
#> 4 1 -13.90 -2.55 0.40597044 -0.3665527 -13.4940296 -2.916553 2
#> 5 1 -14.40 -5.80 0.99030336 -1.0762871 -13.4096966 -6.876287 2
#> 6 1 -3.60 -1.70 0.14650550 -0.7617994 -3.4534945 -2.461799 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -40425 5050
#> initial value 998.131940
#> iter 2 value 796.402308
#> iter 3 value 786.462839
#> iter 4 value 783.330902
#> iter 5 value 752.354794
#> iter 6 value 743.546725
#> iter 7 value 741.822076
#> iter 8 value 741.766938
#> iter 9 value 741.766669
#> iter 10 value 741.766643
#> iter 10 value 741.766642
#> iter 11 value 741.766625
#> iter 11 value 741.766619
#> iter 11 value 741.766616
#> final value 741.766616
#> converged
#> This is Run number 106
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3706653 -0.6501890 -0.1793347 -13.25018899 1
#> 2 1 -0.95 -2.35 -0.1868625 2.7003048 -1.1368625 0.35030479 2
#> 3 1 -6.20 -2.30 2.2690864 4.4052166 -3.9309136 2.10521657 2
#> 4 1 -13.90 -2.55 4.6366917 2.5933194 -9.2633083 0.04331944 2
#> 5 1 -14.40 -5.80 -0.2063270 0.5632061 -14.6063270 -5.23679388 2
#> 6 1 -3.60 -1.70 0.1576100 -0.2597351 -3.4423900 -1.95973514 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38625 7950
#> initial value 998.131940
#> iter 2 value 809.775970
#> iter 3 value 793.933928
#> iter 4 value 792.285217
#> iter 5 value 755.875833
#> iter 6 value 747.431923
#> iter 7 value 746.237832
#> iter 8 value 746.217828
#> iter 9 value 746.217812
#> iter 9 value 746.217809
#> iter 10 value 746.217797
#> iter 10 value 746.217788
#> iter 10 value 746.217786
#> final value 746.217786
#> converged
#> This is Run number 107
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4762951 -0.6836320 0.9262951 -13.2836320 1
#> 2 1 -0.95 -2.35 -0.4807399 1.0827014 -1.4307399 -1.2672986 2
#> 3 1 -6.20 -2.30 0.6813360 1.5812004 -5.5186640 -0.7187996 2
#> 4 1 -13.90 -2.55 1.7734735 2.1870237 -12.1265265 -0.3629763 2
#> 5 1 -14.40 -5.80 -0.9053541 0.3587707 -15.3053541 -5.4412293 2
#> 6 1 -3.60 -1.70 1.4485602 4.7696816 -2.1514398 3.0696816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -38575 7450
#> initial value 998.131940
#> iter 2 value 813.171740
#> iter 3 value 800.922688
#> iter 4 value 800.432948
#> iter 5 value 763.447755
#> iter 6 value 754.915769
#> iter 7 value 753.606315
#> iter 8 value 753.580189
#> iter 9 value 753.580148
#> iter 10 value 753.580135
#> iter 10 value 753.580126
#> iter 10 value 753.580118
#> final value 753.580118
#> converged
#> This is Run number 108
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2464269 2.4212451 0.6964269 -10.178755 1
#> 2 1 -0.95 -2.35 4.4072346 -1.4690220 3.4572346 -3.819022 1
#> 3 1 -6.20 -2.30 1.2752983 0.6047428 -4.9247017 -1.695257 2
#> 4 1 -13.90 -2.55 1.0704427 -0.1757256 -12.8295573 -2.725726 2
#> 5 1 -14.40 -5.80 1.0463270 -0.1008591 -13.3536730 -5.900859 2
#> 6 1 -3.60 -1.70 0.2063991 7.3843605 -3.3936009 5.684360 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -39800 6925
#> initial value 998.131940
#> iter 2 value 797.959726
#> iter 3 value 783.718605
#> iter 4 value 781.325700
#> iter 5 value 748.458307
#> iter 6 value 739.776260
#> iter 7 value 738.507520
#> iter 8 value 738.479953
#> iter 9 value 738.479915
#> iter 9 value 738.479907
#> iter 9 value 738.479901
#> final value 738.479901
#> converged
#> This is Run number 109
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.39172647 -0.05203641 -0.1582735 -12.6520364 1
#> 2 1 -0.95 -2.35 0.35006235 0.18508616 -0.5999376 -2.1649138 1
#> 3 1 -6.20 -2.30 -0.10029407 2.41787591 -6.3002941 0.1178759 2
#> 4 1 -13.90 -2.55 1.26744572 3.91574939 -12.6325543 1.3657494 2
#> 5 1 -14.40 -5.80 -1.26637011 -0.98797537 -15.6663701 -6.7879754 2
#> 6 1 -3.60 -1.70 0.03827256 1.82511702 -3.5617274 0.1251170 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -39400 6775
#> initial value 998.131940
#> iter 2 value 805.087619
#> iter 3 value 790.091283
#> iter 4 value 786.704589
#> iter 5 value 752.878187
#> iter 6 value 744.227483
#> iter 7 value 742.932781
#> iter 8 value 742.904817
#> iter 9 value 742.904778
#> iter 9 value 742.904770
#> iter 9 value 742.904766
#> final value 742.904766
#> converged
#> This is Run number 110
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0910901 0.90853720 -1.6410901 -11.6914628 1
#> 2 1 -0.95 -2.35 1.3017514 -1.00060731 0.3517514 -3.3506073 1
#> 3 1 -6.20 -2.30 1.2648228 -0.05677941 -4.9351772 -2.3567794 2
#> 4 1 -13.90 -2.55 0.3140348 1.90530349 -13.5859652 -0.6446965 2
#> 5 1 -14.40 -5.80 0.2810206 0.57483531 -14.1189794 -5.2251647 2
#> 6 1 -3.60 -1.70 0.7601856 0.34027990 -2.8398144 -1.3597201 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5940 -38125 6575
#> initial value 998.131940
#> iter 2 value 824.912812
#> iter 3 value 812.553499
#> iter 4 value 809.950878
#> iter 5 value 772.140296
#> iter 6 value 763.706414
#> iter 7 value 762.287589
#> iter 8 value 762.257174
#> iter 9 value 762.257121
#> iter 9 value 762.257111
#> iter 9 value 762.257106
#> final value 762.257106
#> converged
#> This is Run number 111
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.8058212 0.5478766 -2.35582117 -12.052123 1
#> 2 1 -0.95 -2.35 0.8956382 3.9970831 -0.05436175 1.647083 2
#> 3 1 -6.20 -2.30 -1.0416625 1.2273396 -7.24166246 -1.072660 2
#> 4 1 -13.90 -2.55 1.2373552 0.3883678 -12.66264480 -2.161632 2
#> 5 1 -14.40 -5.80 2.2001644 1.0020730 -12.19983560 -4.797927 2
#> 6 1 -3.60 -1.70 0.3534812 0.4687166 -3.24651883 -1.231283 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -39400 6700
#> initial value 998.131940
#> iter 2 value 805.065551
#> iter 3 value 793.444220
#> iter 4 value 792.117019
#> iter 5 value 757.657785
#> iter 6 value 748.986708
#> iter 7 value 747.595235
#> iter 8 value 747.562878
#> iter 9 value 747.562819
#> iter 10 value 747.562807
#> iter 10 value 747.562799
#> iter 10 value 747.562793
#> final value 747.562793
#> converged
#> This is Run number 112
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3826689 -1.24161744 0.8326689 -13.8416174 1
#> 2 1 -0.95 -2.35 0.3772576 3.33768768 -0.5727424 0.9876877 2
#> 3 1 -6.20 -2.30 0.2983948 -0.67344002 -5.9016052 -2.9734400 2
#> 4 1 -13.90 -2.55 -0.0890675 3.88421060 -13.9890675 1.3342106 2
#> 5 1 -14.40 -5.80 3.0158876 -0.62171061 -11.3841124 -6.4217106 2
#> 6 1 -3.60 -1.70 0.9935424 -0.08074774 -2.6064576 -1.7807477 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -39875 7375
#> initial value 998.131940
#> iter 2 value 794.308919
#> iter 3 value 778.338280
#> iter 4 value 775.959628
#> iter 5 value 743.431949
#> iter 6 value 734.810346
#> iter 7 value 733.630021
#> iter 8 value 733.607087
#> iter 9 value 733.607066
#> iter 9 value 733.607059
#> iter 9 value 733.607058
#> final value 733.607058
#> converged
#> This is Run number 113
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.3519052 -0.22087558 -0.1980948 -12.8208756 1
#> 2 1 -0.95 -2.35 1.2378199 -0.07860796 0.2878199 -2.4286080 1
#> 3 1 -6.20 -2.30 0.4250086 2.64291920 -5.7749914 0.3429192 2
#> 4 1 -13.90 -2.55 0.6505979 -0.56735223 -13.2494021 -3.1173522 2
#> 5 1 -14.40 -5.80 0.8804580 -0.51777450 -13.5195420 -6.3177745 2
#> 6 1 -3.60 -1.70 0.2589436 -0.02692288 -3.3410564 -1.7269229 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39150 6775
#> initial value 998.131940
#> iter 2 value 808.487918
#> iter 3 value 796.925104
#> iter 4 value 795.689517
#> iter 5 value 760.472944
#> iter 6 value 751.841719
#> iter 7 value 750.448134
#> iter 8 value 750.416367
#> iter 9 value 750.416309
#> iter 10 value 750.416297
#> iter 10 value 750.416288
#> iter 10 value 750.416282
#> final value 750.416282
#> converged
#> This is Run number 114
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.603536490 4.4812340 -1.1535365 -8.11876598 1
#> 2 1 -0.95 -2.35 1.290789430 2.2773126 0.3407894 -0.07268735 1
#> 3 1 -6.20 -2.30 0.003402257 5.9140531 -6.1965977 3.61405310 2
#> 4 1 -13.90 -2.55 2.397009249 0.9084427 -11.5029908 -1.64155726 2
#> 5 1 -14.40 -5.80 0.742565603 -0.4794452 -13.6574344 -6.27944515 2
#> 6 1 -3.60 -1.70 1.486062314 -0.2661207 -2.1139377 -1.96612070 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -37400 6925
#> initial value 998.131940
#> iter 2 value 832.765736
#> iter 3 value 823.424745
#> iter 4 value 823.020686
#> iter 5 value 782.559148
#> iter 6 value 774.309776
#> iter 7 value 772.861929
#> iter 8 value 772.831602
#> iter 9 value 772.831539
#> iter 10 value 772.831523
#> iter 10 value 772.831513
#> iter 10 value 772.831508
#> final value 772.831508
#> converged
#> This is Run number 115
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5331682 1.3911256 -0.0168318 -11.208874 1
#> 2 1 -0.95 -2.35 -1.3483805 1.1460807 -2.2983805 -1.203919 2
#> 3 1 -6.20 -2.30 -0.6134916 0.0323085 -6.8134916 -2.267692 2
#> 4 1 -13.90 -2.55 1.9731837 1.1929599 -11.9268163 -1.357040 2
#> 5 1 -14.40 -5.80 -0.1644487 3.4581791 -14.5644487 -2.341821 2
#> 6 1 -3.60 -1.70 1.6290556 0.4892958 -1.9709444 -1.210704 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37250 6025
#> initial value 998.131940
#> iter 2 value 839.546954
#> iter 3 value 831.298995
#> iter 4 value 830.002911
#> iter 5 value 789.364037
#> iter 6 value 781.212880
#> iter 7 value 779.624756
#> iter 8 value 779.589912
#> iter 9 value 779.589831
#> iter 9 value 779.589820
#> iter 9 value 779.589816
#> final value 779.589816
#> converged
#> This is Run number 116
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.06747118 -1.0469348 -0.4825288 -13.646935 1
#> 2 1 -0.95 -2.35 2.01765020 0.5799595 1.0676502 -1.770041 1
#> 3 1 -6.20 -2.30 -0.75327868 1.0381586 -6.9532787 -1.261841 2
#> 4 1 -13.90 -2.55 0.66372100 1.4667980 -13.2362790 -1.083202 2
#> 5 1 -14.40 -5.80 1.91002904 3.0442269 -12.4899710 -2.755773 2
#> 6 1 -3.60 -1.70 1.64466850 -0.5971875 -1.9553315 -2.297188 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38775 6900
#> initial value 998.131940
#> iter 2 value 813.306633
#> iter 3 value 802.338936
#> iter 4 value 801.590755
#> iter 5 value 765.141387
#> iter 6 value 756.570232
#> iter 7 value 755.161933
#> iter 8 value 755.130457
#> iter 9 value 755.130397
#> iter 10 value 755.130382
#> iter 10 value 755.130372
#> iter 10 value 755.130365
#> final value 755.130365
#> converged
#> This is Run number 117
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4045822 0.4387684 0.8545822 -12.161232 1
#> 2 1 -0.95 -2.35 1.3983074 3.4322257 0.4483074 1.082226 2
#> 3 1 -6.20 -2.30 -1.3395984 0.9512213 -7.5395984 -1.348779 2
#> 4 1 -13.90 -2.55 -0.4738667 -0.5406114 -14.3738667 -3.090611 2
#> 5 1 -14.40 -5.80 -0.6829639 2.0351891 -15.0829639 -3.764811 2
#> 6 1 -3.60 -1.70 1.6339875 3.2106441 -1.9660125 1.510644 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7100 -39175 6575
#> initial value 998.131940
#> iter 2 value 808.623354
#> iter 3 value 799.000421
#> iter 4 value 798.628478
#> iter 5 value 763.169641
#> iter 6 value 754.523404
#> iter 7 value 753.024454
#> iter 8 value 752.987845
#> iter 9 value 752.987760
#> iter 10 value 752.987743
#> iter 10 value 752.987734
#> iter 10 value 752.987727
#> final value 752.987727
#> converged
#> This is Run number 118
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6235698 -0.1444569 -1.1735698 -12.744457 1
#> 2 1 -0.95 -2.35 0.5702282 -0.8272312 -0.3797718 -3.177231 1
#> 3 1 -6.20 -2.30 -0.7591878 4.6361855 -6.9591878 2.336186 2
#> 4 1 -13.90 -2.55 -0.1806253 0.7253241 -14.0806253 -1.824676 2
#> 5 1 -14.40 -5.80 -0.2472027 2.1010108 -14.6472027 -3.698989 2
#> 6 1 -3.60 -1.70 -0.7508465 -0.4454714 -4.3508465 -2.145471 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -38475 7200
#> initial value 998.131940
#> iter 2 value 816.471785
#> iter 3 value 802.714777
#> iter 4 value 800.600099
#> iter 5 value 763.746666
#> iter 6 value 755.268351
#> iter 7 value 753.960391
#> iter 8 value 753.934366
#> iter 9 value 753.934331
#> iter 9 value 753.934320
#> iter 9 value 753.934315
#> final value 753.934315
#> converged
#> This is Run number 119
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.73532364 0.5536026 0.1853236 -12.0463974 1
#> 2 1 -0.95 -2.35 1.06250084 -0.8391651 0.1125008 -3.1891651 1
#> 3 1 -6.20 -2.30 0.13021923 -0.7465294 -6.0697808 -3.0465294 2
#> 4 1 -13.90 -2.55 1.61984241 0.1540740 -12.2801576 -2.3959260 2
#> 5 1 -14.40 -5.80 -0.01241165 4.5142412 -14.4124117 -1.2857588 2
#> 6 1 -3.60 -1.70 -0.76568476 0.9609069 -4.3656848 -0.7390931 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6900 -40675 6575
#> initial value 998.131940
#> iter 2 value 785.510710
#> iter 3 value 772.756777
#> iter 4 value 770.895300
#> iter 5 value 740.440300
#> iter 6 value 731.657421
#> iter 7 value 730.378372
#> iter 8 value 730.347558
#> iter 9 value 730.347508
#> iter 9 value 730.347507
#> iter 9 value 730.347507
#> final value 730.347507
#> converged
#> This is Run number 120
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01594104 4.1415568 -0.5659410 -8.458443 1
#> 2 1 -0.95 -2.35 1.34969009 0.1006979 0.3996901 -2.249302 1
#> 3 1 -6.20 -2.30 -0.82920188 -1.0474885 -7.0292019 -3.347488 2
#> 4 1 -13.90 -2.55 -0.54090910 0.2416173 -14.4409091 -2.308383 2
#> 5 1 -14.40 -5.80 0.03498942 -0.2569341 -14.3650106 -6.056934 2
#> 6 1 -3.60 -1.70 1.45119880 1.4463160 -2.1488012 -0.253684 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -37025 6550
#> initial value 998.131940
#> iter 2 value 840.204456
#> iter 3 value 829.913440
#> iter 4 value 828.081264
#> iter 5 value 786.992376
#> iter 6 value 778.866204
#> iter 7 value 777.423344
#> iter 8 value 777.394222
#> iter 9 value 777.394169
#> iter 9 value 777.394167
#> iter 9 value 777.394167
#> final value 777.394167
#> converged
#> This is Run number 121
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.007398645 -0.6456223 -0.5573986 -13.2456223 1
#> 2 1 -0.95 -2.35 2.755982139 -1.4123493 1.8059821 -3.7623493 1
#> 3 1 -6.20 -2.30 -0.962504418 1.8263480 -7.1625044 -0.4736520 2
#> 4 1 -13.90 -2.55 -0.738591477 -0.4129857 -14.6385915 -2.9629857 2
#> 5 1 -14.40 -5.80 0.921618417 3.8217972 -13.4783816 -1.9782028 2
#> 6 1 -3.60 -1.70 0.368379844 1.0427421 -3.2316202 -0.6572579 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -39000 6425
#> initial value 998.131940
#> iter 2 value 812.553482
#> iter 3 value 801.917743
#> iter 4 value 800.469960
#> iter 5 value 764.820947
#> iter 6 value 756.213543
#> iter 7 value 754.735317
#> iter 8 value 754.700099
#> iter 9 value 754.700025
#> iter 10 value 754.700013
#> iter 10 value 754.700006
#> iter 10 value 754.700006
#> final value 754.700006
#> converged
#> This is Run number 122
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1044082 -1.0239845 0.5544082 -13.6239845 1
#> 2 1 -0.95 -2.35 1.8460893 -0.3844123 0.8960893 -2.7344123 1
#> 3 1 -6.20 -2.30 4.6929555 0.2772338 -1.5070445 -2.0227662 1
#> 4 1 -13.90 -2.55 -0.6429437 1.7768983 -14.5429437 -0.7731017 2
#> 5 1 -14.40 -5.80 0.1151027 -1.2141846 -14.2848973 -7.0141846 2
#> 6 1 -3.60 -1.70 2.2423465 0.3866359 -1.3576535 -1.3133641 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -39975 6725
#> initial value 998.131940
#> iter 2 value 796.078869
#> iter 3 value 783.337508
#> iter 4 value 781.563694
#> iter 5 value 748.983905
#> iter 6 value 740.254234
#> iter 7 value 738.934391
#> iter 8 value 738.903793
#> iter 9 value 738.903743
#> iter 9 value 738.903743
#> iter 9 value 738.903743
#> final value 738.903743
#> converged
#> This is Run number 123
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4958699 0.4953689 -1.0458699 -12.1046311 1
#> 2 1 -0.95 -2.35 0.8843669 2.6466201 -0.0656331 0.2966201 2
#> 3 1 -6.20 -2.30 -0.7861591 0.7865901 -6.9861591 -1.5134099 2
#> 4 1 -13.90 -2.55 -0.8921643 1.7033495 -14.7921643 -0.8466505 2
#> 5 1 -14.40 -5.80 1.3302444 -1.3219559 -13.0697556 -7.1219559 2
#> 6 1 -3.60 -1.70 0.1916989 -0.4053545 -3.4083011 -2.1053545 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38575 5850
#> initial value 998.131940
#> iter 2 value 821.834037
#> iter 3 value 811.011828
#> iter 4 value 808.291189
#> iter 5 value 771.753259
#> iter 6 value 763.214772
#> iter 7 value 761.632365
#> iter 8 value 761.593493
#> iter 9 value 761.593391
#> iter 10 value 761.593378
#> iter 10 value 761.593377
#> iter 10 value 761.593372
#> final value 761.593372
#> converged
#> This is Run number 124
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2104237 0.09877969 -0.7604237 -12.5012203 1
#> 2 1 -0.95 -2.35 2.0589260 1.08507825 1.1089260 -1.2649218 1
#> 3 1 -6.20 -2.30 3.1514716 -0.68329469 -3.0485284 -2.9832947 2
#> 4 1 -13.90 -2.55 1.1270583 -0.62843630 -12.7729417 -3.1784363 2
#> 5 1 -14.40 -5.80 1.4032159 -0.33711845 -12.9967841 -6.1371184 2
#> 6 1 -3.60 -1.70 -0.7215012 1.10637593 -4.3215012 -0.5936241 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -39100 7250
#> initial value 998.131940
#> iter 2 value 807.024467
#> iter 3 value 791.045094
#> iter 4 value 787.929812
#> iter 5 value 753.234479
#> iter 6 value 744.677040
#> iter 7 value 743.436278
#> iter 8 value 743.412094
#> iter 9 value 743.412068
#> iter 9 value 743.412061
#> iter 9 value 743.412056
#> final value 743.412056
#> converged
#> This is Run number 125
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.28295939 1.4161426 -0.2670406 -11.1838574 1
#> 2 1 -0.95 -2.35 2.29162878 1.4828809 1.3416288 -0.8671191 1
#> 3 1 -6.20 -2.30 0.13773400 1.0801234 -6.0622660 -1.2198766 2
#> 4 1 -13.90 -2.55 -1.10820683 0.2308282 -15.0082068 -2.3191718 2
#> 5 1 -14.40 -5.80 -0.02794952 -0.2549103 -14.4279495 -6.0549103 2
#> 6 1 -3.60 -1.70 2.24755125 -1.0006981 -1.3524487 -2.7006981 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -38700 6875
#> initial value 998.131940
#> iter 2 value 815.023033
#> iter 3 value 801.068300
#> iter 4 value 798.261613
#> iter 5 value 762.216639
#> iter 6 value 753.678486
#> iter 7 value 752.342646
#> iter 8 value 752.314655
#> iter 9 value 752.314615
#> iter 9 value 752.314606
#> iter 9 value 752.314601
#> final value 752.314601
#> converged
#> This is Run number 126
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1859691 -0.8381323 2.6359691 -13.4381323 1
#> 2 1 -0.95 -2.35 1.1883152 -0.8078310 0.2383152 -3.1578310 1
#> 3 1 -6.20 -2.30 0.7620435 3.6183367 -5.4379565 1.3183367 2
#> 4 1 -13.90 -2.55 1.0069732 1.9725617 -12.8930268 -0.5774383 2
#> 5 1 -14.40 -5.80 -0.2800473 1.2369484 -14.6800473 -4.5630516 2
#> 6 1 -3.60 -1.70 4.4138473 3.1231985 0.8138473 1.4231985 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -38775 6575
#> initial value 998.131940
#> iter 2 value 815.460942
#> iter 3 value 802.537169
#> iter 4 value 799.819079
#> iter 5 value 763.925311
#> iter 6 value 755.356496
#> iter 7 value 753.959953
#> iter 8 value 753.928901
#> iter 9 value 753.928847
#> iter 9 value 753.928837
#> iter 9 value 753.928832
#> final value 753.928832
#> converged
#> This is Run number 127
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4704153 1.705396125 -0.07958474 -10.8946039 1
#> 2 1 -0.95 -2.35 0.2806316 0.007796026 -0.66936843 -2.3422040 1
#> 3 1 -6.20 -2.30 0.6016990 1.967345465 -5.59830097 -0.3326545 2
#> 4 1 -13.90 -2.55 0.6087371 0.352152908 -13.29126289 -2.1978471 2
#> 5 1 -14.40 -5.80 1.9502347 0.965958981 -12.44976534 -4.8340410 2
#> 6 1 -3.60 -1.70 -0.9923503 -0.619029628 -4.59235026 -2.3190296 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -39575 7700
#> initial value 998.131940
#> iter 2 value 796.921234
#> iter 3 value 781.307460
#> iter 4 value 779.870670
#> iter 5 value 746.228503
#> iter 6 value 737.641984
#> iter 7 value 736.469027
#> iter 8 value 736.447753
#> iter 8 value 736.447749
#> final value 736.447749
#> converged
#> This is Run number 128
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6155602 0.30384009 1.0655602 -12.2961599 1
#> 2 1 -0.95 -2.35 0.7574315 -0.61876202 -0.1925685 -2.9687620 1
#> 3 1 -6.20 -2.30 1.9302551 2.70334303 -4.2697449 0.4033430 2
#> 4 1 -13.90 -2.55 0.5040528 0.10378346 -13.3959472 -2.4462165 2
#> 5 1 -14.40 -5.80 0.6823083 0.04999199 -13.7176917 -5.7500080 2
#> 6 1 -3.60 -1.70 0.2407718 1.10703430 -3.3592282 -0.5929657 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37950 5925
#> initial value 998.131940
#> iter 2 value 830.175463
#> iter 3 value 821.900026
#> iter 4 value 820.671042
#> iter 5 value 781.912269
#> iter 6 value 773.571604
#> iter 7 value 771.931159
#> iter 8 value 771.892446
#> iter 9 value 771.892347
#> iter 10 value 771.892335
#> iter 10 value 771.892331
#> iter 10 value 771.892327
#> final value 771.892327
#> converged
#> This is Run number 129
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.013257058 0.6146410 -0.5367429 -11.9853590 1
#> 2 1 -0.95 -2.35 -0.007590402 -0.2269947 -0.9575904 -2.5769947 1
#> 3 1 -6.20 -2.30 -0.129764150 -0.4604442 -6.3297641 -2.7604442 2
#> 4 1 -13.90 -2.55 -0.826629694 0.6566235 -14.7266297 -1.8933765 2
#> 5 1 -14.40 -5.80 0.925438344 -0.3550511 -13.4745617 -6.1550511 2
#> 6 1 -3.60 -1.70 0.523862051 1.2371312 -3.0761379 -0.4628688 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -38925 6375
#> initial value 998.131940
#> iter 2 value 813.935764
#> iter 3 value 803.434884
#> iter 4 value 801.941989
#> iter 5 value 766.082142
#> iter 6 value 757.489358
#> iter 7 value 755.997046
#> iter 8 value 755.961420
#> iter 9 value 755.961344
#> iter 10 value 755.961332
#> iter 10 value 755.961325
#> iter 10 value 755.961325
#> final value 755.961325
#> converged
#> This is Run number 130
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.28706691 0.08503725 -0.8370669 -12.5149627 1
#> 2 1 -0.95 -2.35 0.72972559 1.68337268 -0.2202744 -0.6666273 1
#> 3 1 -6.20 -2.30 1.29963033 -0.42474723 -4.9003697 -2.7247472 2
#> 4 1 -13.90 -2.55 1.16782494 4.82519673 -12.7321751 2.2751967 2
#> 5 1 -14.40 -5.80 -0.03524421 -0.37960836 -14.4352442 -6.1796084 2
#> 6 1 -3.60 -1.70 -0.63969585 -0.34121831 -4.2396959 -2.0412183 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -38225 6475
#> initial value 998.131940
#> iter 2 value 823.840237
#> iter 3 value 813.092715
#> iter 4 value 811.346496
#> iter 5 value 773.561946
#> iter 6 value 765.116619
#> iter 7 value 763.642130
#> iter 8 value 763.609118
#> iter 9 value 763.609052
#> iter 9 value 763.609052
#> iter 9 value 763.609052
#> final value 763.609052
#> converged
#> This is Run number 131
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.3165315 1.524189532 -0.8665315 -11.075810 1
#> 2 1 -0.95 -2.35 1.3164826 0.652308434 0.3664826 -1.697692 1
#> 3 1 -6.20 -2.30 -1.4117486 -0.016456106 -7.6117486 -2.316456 2
#> 4 1 -13.90 -2.55 -0.2352694 -0.080260767 -14.1352694 -2.630261 2
#> 5 1 -14.40 -5.80 0.6037892 0.500541109 -13.7962108 -5.299459 2
#> 6 1 -3.60 -1.70 0.4378517 -0.009254014 -3.1621483 -1.709254 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -39075 8575
#> initial value 998.131940
#> iter 2 value 799.060048
#> iter 3 value 778.598971
#> iter 4 value 775.824969
#> iter 5 value 741.258481
#> iter 6 value 732.942168
#> iter 7 value 731.848667
#> iter 8 value 731.833511
#> iter 9 value 731.833497
#> iter 9 value 731.833494
#> iter 9 value 731.833494
#> final value 731.833494
#> converged
#> This is Run number 132
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5196768 0.5890659 -1.0696768 -12.01093412 1
#> 2 1 -0.95 -2.35 0.8236607 -0.2641049 -0.1263393 -2.61410492 1
#> 3 1 -6.20 -2.30 4.4109768 -0.1255354 -1.7890232 -2.42553541 1
#> 4 1 -13.90 -2.55 -0.7794212 0.3924532 -14.6794212 -2.15754678 2
#> 5 1 -14.40 -5.80 1.3540949 0.4193582 -13.0459051 -5.38064184 2
#> 6 1 -3.60 -1.70 1.4265360 1.6007162 -2.1734640 -0.09928384 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -36525 7175
#> initial value 998.131940
#> iter 2 value 843.439420
#> iter 3 value 832.706472
#> iter 4 value 831.328997
#> iter 5 value 788.744654
#> iter 6 value 780.755104
#> iter 7 value 779.414690
#> iter 8 value 779.390285
#> iter 9 value 779.390248
#> iter 10 value 779.390236
#> iter 10 value 779.390225
#> iter 10 value 779.390220
#> final value 779.390220
#> converged
#> This is Run number 133
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6985852 -0.3486969 -1.2485852 -12.9486969 1
#> 2 1 -0.95 -2.35 0.3226493 -0.5028395 -0.6273507 -2.8528395 1
#> 3 1 -6.20 -2.30 3.4734443 0.4955129 -2.7265557 -1.8044871 2
#> 4 1 -13.90 -2.55 0.2666107 0.7923951 -13.6333893 -1.7576049 2
#> 5 1 -14.40 -5.80 1.4734701 4.4063127 -12.9265299 -1.3936873 2
#> 6 1 -3.60 -1.70 -0.1324955 1.1545845 -3.7324955 -0.5454155 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5340 -36175 7200
#> initial value 998.131940
#> iter 2 value 847.822259
#> iter 3 value 836.129674
#> iter 4 value 834.008898
#> iter 5 value 790.676626
#> iter 6 value 782.794608
#> iter 7 value 781.486977
#> iter 8 value 781.464486
#> iter 9 value 781.464457
#> iter 9 value 781.464447
#> iter 9 value 781.464442
#> final value 781.464442
#> converged
#> This is Run number 134
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.87286352 -0.6392067 0.3228635 -13.239207 1
#> 2 1 -0.95 -2.35 1.75347823 -0.2807660 0.8034782 -2.630766 1
#> 3 1 -6.20 -2.30 0.52224873 1.0334426 -5.6777513 -1.266557 2
#> 4 1 -13.90 -2.55 -0.78541897 -1.0078416 -14.6854190 -3.557842 2
#> 5 1 -14.40 -5.80 -0.54515703 1.2838356 -14.9451570 -4.516164 2
#> 6 1 -3.60 -1.70 0.02167894 -1.7751504 -3.5783211 -3.475150 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -36525 7650
#> initial value 998.131940
#> iter 2 value 840.601584
#> iter 3 value 829.543291
#> iter 4 value 828.768332
#> iter 5 value 785.997373
#> iter 6 value 777.977331
#> iter 7 value 776.688733
#> iter 8 value 776.666672
#> iter 9 value 776.666641
#> iter 9 value 776.666629
#> iter 9 value 776.666624
#> final value 776.666624
#> converged
#> This is Run number 135
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8856850 -0.41886283 0.335685 -13.0188628 1
#> 2 1 -0.95 -2.35 -0.7252232 0.51405599 -1.675223 -1.8359440 1
#> 3 1 -6.20 -2.30 0.3163594 0.41299380 -5.883641 -1.8870062 2
#> 4 1 -13.90 -2.55 1.9515774 -0.08487522 -11.948423 -2.6348752 2
#> 5 1 -14.40 -5.80 1.2379621 -0.57006197 -13.162038 -6.3700620 2
#> 6 1 -3.60 -1.70 0.3179838 2.16273940 -3.282016 0.4627394 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -37075 6825
#> initial value 998.131940
#> iter 2 value 838.047265
#> iter 3 value 827.742923
#> iter 4 value 826.366996
#> iter 5 value 785.280305
#> iter 6 value 777.135385
#> iter 7 value 775.723808
#> iter 8 value 775.695699
#> iter 9 value 775.695649
#> iter 9 value 775.695649
#> iter 9 value 775.695649
#> final value 775.695649
#> converged
#> This is Run number 136
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.23167818 2.42646006 1.681678 -10.1735399 1
#> 2 1 -0.95 -2.35 2.01476686 0.47271232 1.064767 -1.8772877 1
#> 3 1 -6.20 -2.30 -0.20470875 0.05081534 -6.404709 -2.2491847 2
#> 4 1 -13.90 -2.55 2.29210249 -0.08752552 -11.607898 -2.6375255 2
#> 5 1 -14.40 -5.80 0.64678624 -0.08449036 -13.753214 -5.8844904 2
#> 6 1 -3.60 -1.70 -0.09931459 1.05061407 -3.699315 -0.6493859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38825 8150
#> initial value 998.131940
#> iter 2 value 805.572942
#> iter 3 value 788.489731
#> iter 4 value 786.670826
#> iter 5 value 750.959618
#> iter 6 value 742.528961
#> iter 7 value 741.373855
#> iter 8 value 741.355702
#> iter 9 value 741.355687
#> iter 9 value 741.355684
#> iter 9 value 741.355675
#> final value 741.355675
#> converged
#> This is Run number 137
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8511228 -0.02889434 0.30112281 -12.628894 1
#> 2 1 -0.95 -2.35 0.9178843 -0.43448110 -0.03211565 -2.784481 1
#> 3 1 -6.20 -2.30 -0.7812737 0.33578475 -6.98127367 -1.964215 2
#> 4 1 -13.90 -2.55 1.1838083 0.12798655 -12.71619170 -2.422013 2
#> 5 1 -14.40 -5.80 1.4619885 1.73312689 -12.93801148 -4.066873 2
#> 6 1 -3.60 -1.70 -0.5712750 2.11494896 -4.17127502 0.414949 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38925 7200
#> initial value 998.131940
#> iter 2 value 809.612017
#> iter 3 value 796.934252
#> iter 4 value 795.808298
#> iter 5 value 759.981885
#> iter 6 value 751.403569
#> iter 7 value 750.085991
#> iter 8 value 750.058522
#> iter 9 value 750.058480
#> iter 10 value 750.058468
#> iter 10 value 750.058458
#> iter 10 value 750.058452
#> final value 750.058452
#> converged
#> This is Run number 138
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8205621 0.3040667 0.2705621 -12.2959333 1
#> 2 1 -0.95 -2.35 0.6763085 2.0613613 -0.2736915 -0.2886387 1
#> 3 1 -6.20 -2.30 1.1298120 -0.1978730 -5.0701880 -2.4978730 2
#> 4 1 -13.90 -2.55 -0.9525673 0.1635724 -14.8525673 -2.3864276 2
#> 5 1 -14.40 -5.80 -0.1402400 0.8233854 -14.5402400 -4.9766146 2
#> 6 1 -3.60 -1.70 -0.6453974 0.0574075 -4.2453974 -1.6425925 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7020 -39900 7525
#> initial value 998.131940
#> iter 2 value 792.314353
#> iter 3 value 778.832828
#> iter 4 value 778.545369
#> iter 5 value 745.526780
#> iter 6 value 736.825756
#> iter 7 value 735.615245
#> iter 8 value 735.591317
#> iter 9 value 735.591286
#> iter 9 value 735.591278
#> iter 9 value 735.591276
#> final value 735.591276
#> converged
#> This is Run number 139
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.58365874 -0.09696646 0.03365874 -12.6969665 1
#> 2 1 -0.95 -2.35 -0.97517770 0.86955234 -1.92517770 -1.4804477 2
#> 3 1 -6.20 -2.30 -1.63648937 1.65310178 -7.83648937 -0.6468982 2
#> 4 1 -13.90 -2.55 -0.02224711 -0.20563262 -13.92224711 -2.7556326 2
#> 5 1 -14.40 -5.80 4.36404999 1.41800687 -10.03595001 -4.3819931 2
#> 6 1 -3.60 -1.70 2.28158734 -1.17624436 -1.31841266 -2.8762444 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5880 -38400 8225
#> initial value 998.131940
#> iter 2 value 811.283694
#> iter 3 value 794.969622
#> iter 4 value 793.501579
#> iter 5 value 756.400747
#> iter 6 value 748.013795
#> iter 7 value 746.843840
#> iter 8 value 746.825819
#> iter 9 value 746.825806
#> iter 9 value 746.825803
#> iter 9 value 746.825792
#> final value 746.825792
#> converged
#> This is Run number 140
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1195485 -0.99575207 -0.4304515 -13.595752 1
#> 2 1 -0.95 -2.35 -1.0843589 -0.52583176 -2.0343589 -2.875832 1
#> 3 1 -6.20 -2.30 1.9381947 -0.71982923 -4.2618053 -3.019829 2
#> 4 1 -13.90 -2.55 0.1439180 0.52312576 -13.7560820 -2.026874 2
#> 5 1 -14.40 -5.80 -0.2379121 -0.05483515 -14.6379121 -5.854835 2
#> 6 1 -3.60 -1.70 -0.5339392 -0.27023570 -4.1339392 -1.970236 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -35975 6100
#> initial value 998.131940
#> iter 2 value 855.726129
#> iter 3 value 849.449133
#> iter 4 value 848.985625
#> iter 5 value 804.812668
#> iter 6 value 797.105243
#> iter 7 value 795.568336
#> iter 8 value 795.538065
#> iter 9 value 795.537995
#> iter 9 value 795.537989
#> iter 9 value 795.537989
#> final value 795.537989
#> converged
#> This is Run number 141
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5204681 -0.8373088 -0.02953187 -13.437309 1
#> 2 1 -0.95 -2.35 0.8694662 0.3745249 -0.08053376 -1.975475 1
#> 3 1 -6.20 -2.30 2.4218607 -0.4524521 -3.77813930 -2.752452 2
#> 4 1 -13.90 -2.55 0.1557874 1.0736752 -13.74421264 -1.476325 2
#> 5 1 -14.40 -5.80 -1.2387726 0.7329548 -15.63877263 -5.067045 2
#> 6 1 -3.60 -1.70 2.2043552 -0.4960609 -1.39564481 -2.196061 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -38050 6325
#> initial value 998.131940
#> iter 2 value 827.024049
#> iter 3 value 817.163741
#> iter 4 value 815.642434
#> iter 5 value 777.278519
#> iter 6 value 768.882294
#> iter 7 value 767.360503
#> iter 8 value 767.326015
#> iter 9 value 767.325941
#> iter 10 value 767.325929
#> iter 10 value 767.325922
#> iter 10 value 767.325917
#> final value 767.325917
#> converged
#> This is Run number 142
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9356484 1.3688998 0.3856484 -11.2311002 1
#> 2 1 -0.95 -2.35 2.0059175 2.6400638 1.0559175 0.2900638 1
#> 3 1 -6.20 -2.30 0.2949954 -0.4800333 -5.9050046 -2.7800333 2
#> 4 1 -13.90 -2.55 -1.2173447 2.3460072 -15.1173447 -0.2039928 2
#> 5 1 -14.40 -5.80 -0.4629034 1.3966766 -14.8629034 -4.4033234 2
#> 6 1 -3.60 -1.70 0.1672113 0.6482633 -3.4327887 -1.0517367 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -38125 6775
#> initial value 998.131940
#> iter 2 value 823.649927
#> iter 3 value 812.860074
#> iter 4 value 811.623783
#> iter 5 value 773.423588
#> iter 6 value 764.999157
#> iter 7 value 763.567407
#> iter 8 value 763.536394
#> iter 9 value 763.536335
#> iter 10 value 763.536322
#> iter 10 value 763.536312
#> iter 10 value 763.536308
#> final value 763.536308
#> converged
#> This is Run number 143
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01623733 4.4900386 -0.5662373 -8.1099614 1
#> 2 1 -0.95 -2.35 0.14646683 -0.1479136 -0.8035332 -2.4979136 1
#> 3 1 -6.20 -2.30 0.55993888 0.2951670 -5.6400611 -2.0048330 2
#> 4 1 -13.90 -2.55 1.57540644 1.7172438 -12.3245936 -0.8327562 2
#> 5 1 -14.40 -5.80 0.61582758 4.2606734 -13.7841724 -1.5393266 2
#> 6 1 -3.60 -1.70 0.06077692 2.0014828 -3.5392231 0.3014828 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38850 8000
#> initial value 998.131940
#> iter 2 value 806.102722
#> iter 3 value 790.137963
#> iter 4 value 788.714221
#> iter 5 value 752.930872
#> iter 6 value 744.455297
#> iter 7 value 743.278152
#> iter 8 value 743.258637
#> iter 9 value 743.258617
#> iter 9 value 743.258613
#> iter 9 value 743.258606
#> final value 743.258606
#> converged
#> This is Run number 144
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.02540204 0.08516046 -0.5754020 -12.5148395 1
#> 2 1 -0.95 -2.35 0.12932325 -0.08493782 -0.8206767 -2.4349378 1
#> 3 1 -6.20 -2.30 0.94974298 -0.92341321 -5.2502570 -3.2234132 2
#> 4 1 -13.90 -2.55 5.45093184 0.97000046 -8.4490682 -1.5799995 2
#> 5 1 -14.40 -5.80 0.68751333 -0.09983055 -13.7124867 -5.8998306 2
#> 6 1 -3.60 -1.70 1.06535369 0.74274411 -2.5346463 -0.9572559 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39550 7625
#> initial value 998.131940
#> iter 2 value 797.674010
#> iter 3 value 782.801550
#> iter 4 value 781.654072
#> iter 5 value 747.826941
#> iter 6 value 739.216033
#> iter 7 value 738.022354
#> iter 8 value 738.000025
#> iter 9 value 738.000002
#> iter 9 value 737.999994
#> iter 9 value 737.999991
#> final value 737.999991
#> converged
#> This is Run number 145
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1425866 1.0008970 -0.4074134 -11.5991030 1
#> 2 1 -0.95 -2.35 -1.1802779 1.6102184 -2.1302779 -0.7397816 2
#> 3 1 -6.20 -2.30 0.7753154 -0.2292162 -5.4246846 -2.5292162 2
#> 4 1 -13.90 -2.55 -1.2358724 0.9545549 -15.1358724 -1.5954451 2
#> 5 1 -14.40 -5.80 -0.9534038 2.0717363 -15.3534038 -3.7282637 2
#> 6 1 -3.60 -1.70 1.8562992 -0.3633814 -1.7437008 -2.0633814 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39275 6850
#> initial value 998.131940
#> iter 2 value 806.619959
#> iter 3 value 790.947770
#> iter 4 value 787.259675
#> iter 5 value 753.144637
#> iter 6 value 744.515946
#> iter 7 value 743.238137
#> iter 8 value 743.211328
#> iter 9 value 743.211293
#> iter 9 value 743.211286
#> iter 9 value 743.211281
#> final value 743.211281
#> converged
#> This is Run number 146
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2867370 -0.9313730 -0.83673697 -13.531373 1
#> 2 1 -0.95 -2.35 0.8640782 0.5480416 -0.08592184 -1.801958 1
#> 3 1 -6.20 -2.30 -1.4136972 0.6295673 -7.61369720 -1.670433 2
#> 4 1 -13.90 -2.55 1.1147061 0.4361971 -12.78529389 -2.113803 2
#> 5 1 -14.40 -5.80 2.4387189 0.3467111 -11.96128112 -5.453289 2
#> 6 1 -3.60 -1.70 0.6153004 -0.8356694 -2.98469961 -2.535669 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38000 6950
#> initial value 998.131940
#> iter 2 value 824.432157
#> iter 3 value 813.690608
#> iter 4 value 812.771878
#> iter 5 value 774.140127
#> iter 6 value 765.740075
#> iter 7 value 764.328791
#> iter 8 value 764.298907
#> iter 9 value 764.298852
#> iter 10 value 764.298837
#> iter 10 value 764.298827
#> iter 10 value 764.298824
#> final value 764.298824
#> converged
#> This is Run number 147
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.24351930 2.14403611 -1.793519 -10.4559639 1
#> 2 1 -0.95 -2.35 2.90579605 -0.09093662 1.955796 -2.4409366 1
#> 3 1 -6.20 -2.30 0.69668368 0.41219840 -5.503316 -1.8878016 2
#> 4 1 -13.90 -2.55 0.05818041 0.10300689 -13.841820 -2.4469931 2
#> 5 1 -14.40 -5.80 -1.29087069 -0.81303065 -15.690871 -6.6130307 2
#> 6 1 -3.60 -1.70 1.35727580 1.41340633 -2.242724 -0.2865937 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -39350 7225
#> initial value 998.131940
#> iter 2 value 803.207714
#> iter 3 value 789.025029
#> iter 4 value 787.183568
#> iter 5 value 752.857580
#> iter 6 value 744.242693
#> iter 7 value 742.980120
#> iter 8 value 742.954307
#> iter 9 value 742.954274
#> iter 9 value 742.954264
#> iter 9 value 742.954258
#> final value 742.954258
#> converged
#> This is Run number 148
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.19733318 0.51077804 0.6473332 -12.0892220 1
#> 2 1 -0.95 -2.35 -0.52125916 2.13107625 -1.4712592 -0.2189238 2
#> 3 1 -6.20 -2.30 -0.18981702 -0.03074734 -6.3898170 -2.3307473 2
#> 4 1 -13.90 -2.55 1.64015825 3.01803842 -12.2598417 0.4680384 2
#> 5 1 -14.40 -5.80 0.03052362 -0.57099509 -14.3694764 -6.3709951 2
#> 6 1 -3.60 -1.70 1.33886210 -0.39531734 -2.2611379 -2.0953173 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5620 -37600 8125
#> initial value 998.131940
#> iter 2 value 823.285079
#> iter 3 value 808.031135
#> iter 4 value 806.333951
#> iter 5 value 766.884280
#> iter 6 value 758.633079
#> iter 7 value 757.422678
#> iter 8 value 757.403788
#> iter 9 value 757.403772
#> iter 9 value 757.403772
#> iter 9 value 757.403766
#> final value 757.403766
#> converged
#> This is Run number 149
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.43609393 0.7013268 -0.1139061 -11.8986732 1
#> 2 1 -0.95 -2.35 -1.11922853 3.1194979 -2.0692285 0.7694979 2
#> 3 1 -6.20 -2.30 0.06393889 1.0611855 -6.1360611 -1.2388145 2
#> 4 1 -13.90 -2.55 0.79532654 3.7323890 -13.1046735 1.1823890 2
#> 5 1 -14.40 -5.80 -1.15528773 0.2589116 -15.5552877 -5.5410884 2
#> 6 1 -3.60 -1.70 2.16473543 1.4874184 -1.4352646 -0.2125816 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5320 -35950 6950
#> initial value 998.131940
#> iter 2 value 852.058458
#> iter 3 value 841.022494
#> iter 4 value 838.842118
#> iter 5 value 794.959638
#> iter 6 value 787.156416
#> iter 7 value 785.830916
#> iter 8 value 785.807907
#> iter 9 value 785.807875
#> iter 9 value 785.807866
#> iter 9 value 785.807862
#> final value 785.807862
#> converged
#> This is Run number 150
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1925067 2.04015897 -0.7425067 -10.5598410 1
#> 2 1 -0.95 -2.35 0.1776420 0.05961709 -0.7723580 -2.2903829 1
#> 3 1 -6.20 -2.30 1.7347755 -0.47444233 -4.4652245 -2.7744423 2
#> 4 1 -13.90 -2.55 -0.3297786 1.79303070 -14.2297786 -0.7569693 2
#> 5 1 -14.40 -5.80 0.7295488 0.46424627 -13.6704512 -5.3357537 2
#> 6 1 -3.60 -1.70 -0.3886173 0.29899326 -3.9886173 -1.4010067 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -38450 6275
#> initial value 998.131940
#> iter 2 value 821.505696
#> iter 3 value 811.331868
#> iter 4 value 809.670627
#> iter 5 value 772.483885
#> iter 6 value 763.991729
#> iter 7 value 762.467864
#> iter 8 value 762.432221
#> iter 9 value 762.432143
#> iter 10 value 762.432131
#> iter 10 value 762.432125
#> iter 10 value 762.432123
#> final value 762.432123
#> converged
#> This is Run number 151
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5600606 1.33529786 -1.1100606 -11.264702 1
#> 2 1 -0.95 -2.35 2.4614802 0.16456444 1.5114802 -2.185436 1
#> 3 1 -6.20 -2.30 -0.6452466 -1.11798262 -6.8452466 -3.417983 2
#> 4 1 -13.90 -2.55 -0.2636248 -0.79869186 -14.1636248 -3.348692 2
#> 5 1 -14.40 -5.80 -0.2024300 2.80931145 -14.6024300 -2.990689 2
#> 6 1 -3.60 -1.70 2.7816691 -0.07894998 -0.8183309 -1.778950 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38025 6725
#> initial value 998.131940
#> iter 2 value 825.384958
#> iter 3 value 814.547207
#> iter 4 value 813.129980
#> iter 5 value 774.696324
#> iter 6 value 766.297102
#> iter 7 value 764.861318
#> iter 8 value 764.830368
#> iter 9 value 764.830311
#> iter 9 value 764.830311
#> iter 9 value 764.830311
#> final value 764.830311
#> converged
#> This is Run number 152
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6250066 0.2262293 -1.175007 -12.3737707 1
#> 2 1 -0.95 -2.35 3.3231726 -0.6459198 2.373173 -2.9959198 1
#> 3 1 -6.20 -2.30 -0.5017023 1.5260813 -6.701702 -0.7739187 2
#> 4 1 -13.90 -2.55 0.5679645 0.1826057 -13.332035 -2.3673943 2
#> 5 1 -14.40 -5.80 0.9951574 -0.4104710 -13.404843 -6.2104710 2
#> 6 1 -3.60 -1.70 1.8083609 -1.3865536 -1.791639 -3.0865536 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 4860 -35025 6700
#> initial value 998.131940
#> iter 2 value 864.561788
#> iter 3 value 853.366007
#> iter 4 value 850.618570
#> iter 5 value 804.486120
#> iter 6 value 796.982491
#> iter 7 value 795.705861
#> iter 8 value 795.685667
#> iter 9 value 795.685642
#> iter 9 value 795.685636
#> iter 9 value 795.685633
#> final value 795.685633
#> converged
#> This is Run number 153
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2870767 -0.02050144 -0.8370767 -12.620501 1
#> 2 1 -0.95 -2.35 0.1221351 1.23251082 -0.8278649 -1.117489 1
#> 3 1 -6.20 -2.30 1.0288343 0.70349491 -5.1711657 -1.596505 2
#> 4 1 -13.90 -2.55 -0.7415543 0.29205276 -14.6415543 -2.257947 2
#> 5 1 -14.40 -5.80 -0.5924580 -0.16841918 -14.9924580 -5.968419 2
#> 6 1 -3.60 -1.70 -1.3418374 -0.60850812 -4.9418374 -2.308508 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -36925 7325
#> initial value 998.131940
#> iter 2 value 837.353294
#> iter 3 value 823.886922
#> iter 4 value 821.325484
#> iter 5 value 780.150321
#> iter 6 value 772.039706
#> iter 7 value 770.738327
#> iter 8 value 770.715401
#> iter 9 value 770.715374
#> iter 9 value 770.715364
#> iter 9 value 770.715359
#> final value 770.715359
#> converged
#> This is Run number 154
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.53920613 0.4633758 0.9892061 -12.1366242 1
#> 2 1 -0.95 -2.35 1.71380230 -0.4433767 0.7638023 -2.7933767 1
#> 3 1 -6.20 -2.30 0.03696869 1.8820436 -6.1630313 -0.4179564 2
#> 4 1 -13.90 -2.55 0.19547196 6.2942176 -13.7045280 3.7442176 2
#> 5 1 -14.40 -5.80 -0.88588605 -0.7344021 -15.2858860 -6.5344021 2
#> 6 1 -3.60 -1.70 0.65747306 -0.3554803 -2.9425269 -2.0554803 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6880 -37700 5775
#> initial value 998.131940
#> iter 2 value 834.023460
#> iter 3 value 827.284290
#> iter 4 value 826.728475
#> iter 5 value 787.034662
#> iter 6 value 778.799035
#> iter 7 value 777.075526
#> iter 8 value 777.034725
#> iter 9 value 777.034609
#> iter 10 value 777.034597
#> iter 10 value 777.034592
#> iter 10 value 777.034587
#> final value 777.034587
#> converged
#> This is Run number 155
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.9846353 2.0813401 -1.5346353 -10.518660 1
#> 2 1 -0.95 -2.35 0.3228183 -1.2500166 -0.6271817 -3.600017 1
#> 3 1 -6.20 -2.30 1.3564790 -0.5968467 -4.8435210 -2.896847 2
#> 4 1 -13.90 -2.55 0.3135420 -0.1155842 -13.5864580 -2.665584 2
#> 5 1 -14.40 -5.80 1.5523309 0.1802541 -12.8476691 -5.619746 2
#> 6 1 -3.60 -1.70 1.4359782 -1.2105459 -2.1640218 -2.910546 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6760 -39075 7000
#> initial value 998.131940
#> iter 2 value 808.235077
#> iter 3 value 796.796033
#> iter 4 value 796.120122
#> iter 5 value 760.557113
#> iter 6 value 751.932193
#> iter 7 value 750.559096
#> iter 8 value 750.528560
#> iter 9 value 750.528505
#> iter 10 value 750.528490
#> iter 10 value 750.528480
#> iter 10 value 750.528473
#> final value 750.528473
#> converged
#> This is Run number 156
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3284442 -0.8323573 0.7784442 -13.432357 1
#> 2 1 -0.95 -2.35 -0.2553660 -0.1226016 -1.2053660 -2.472602 1
#> 3 1 -6.20 -2.30 0.9513305 2.0407260 -5.2486695 -0.259274 2
#> 4 1 -13.90 -2.55 1.8509883 1.2119672 -12.0490117 -1.338033 2
#> 5 1 -14.40 -5.80 0.2170416 0.6717132 -14.1829584 -5.128287 2
#> 6 1 -3.60 -1.70 -0.5796611 0.1742366 -4.1796611 -1.525763 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6520 -38875 7475
#> initial value 998.131940
#> iter 2 value 808.688095
#> iter 3 value 795.657059
#> iter 4 value 794.915069
#> iter 5 value 758.892339
#> iter 6 value 750.324033
#> iter 7 value 749.044868
#> iter 8 value 749.019613
#> iter 9 value 749.019578
#> iter 10 value 749.019566
#> iter 10 value 749.019557
#> iter 10 value 749.019549
#> final value 749.019549
#> converged
#> This is Run number 157
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1196599 0.3701395 -0.4303401 -12.22986050 1
#> 2 1 -0.95 -2.35 1.8375022 2.0634689 0.8875022 -0.28653107 1
#> 3 1 -6.20 -2.30 -0.2368146 0.5991558 -6.4368146 -1.70084418 2
#> 4 1 -13.90 -2.55 -0.7280566 1.1624193 -14.6280566 -1.38758066 2
#> 5 1 -14.40 -5.80 1.6802103 -0.1810604 -12.7197897 -5.98106041 2
#> 6 1 -3.60 -1.70 -0.1156988 1.7546507 -3.7156988 0.05465075 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -40075 5850
#> initial value 998.131940
#> iter 2 value 798.311202
#> iter 3 value 789.045381
#> iter 4 value 787.698957
#> iter 5 value 755.128609
#> iter 6 value 746.366016
#> iter 7 value 744.780987
#> iter 8 value 744.737392
#> iter 9 value 744.737272
#> iter 10 value 744.737259
#> iter 10 value 744.737259
#> iter 10 value 744.737252
#> final value 744.737252
#> converged
#> This is Run number 158
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.01687771 -0.1186750 -0.5668777 -12.718675 1
#> 2 1 -0.95 -2.35 -0.31483839 1.2810316 -1.2648384 -1.068968 2
#> 3 1 -6.20 -2.30 1.48161290 0.6009233 -4.7183871 -1.699077 2
#> 4 1 -13.90 -2.55 -0.34127499 0.5603407 -14.2412750 -1.989659 2
#> 5 1 -14.40 -5.80 -0.85863450 -1.4289316 -15.2586345 -7.228932 2
#> 6 1 -3.60 -1.70 -0.69124424 0.3564565 -4.2912442 -1.343544 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5580 -37725 6075
#> initial value 998.131940
#> iter 2 value 833.062560
#> iter 3 value 819.839446
#> iter 4 value 816.162791
#> iter 5 value 777.306314
#> iter 6 value 768.889047
#> iter 7 value 767.425852
#> iter 8 value 767.394077
#> iter 9 value 767.394008
#> iter 9 value 767.393996
#> iter 9 value 767.393991
#> final value 767.393991
#> converged
#> This is Run number 159
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.6252827 1.56392814 1.0752827 -11.036072 1
#> 2 1 -0.95 -2.35 1.6101609 -0.70950821 0.6601609 -3.059508 1
#> 3 1 -6.20 -2.30 0.3404632 1.94502896 -5.8595368 -0.354971 2
#> 4 1 -13.90 -2.55 1.7445505 -0.45246603 -12.1554495 -3.002466 2
#> 5 1 -14.40 -5.80 2.3145823 3.10005494 -12.0854177 -2.699945 2
#> 6 1 -3.60 -1.70 -0.3846931 -0.07749941 -3.9846931 -1.777499 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -38825 7325
#> initial value 998.131940
#> iter 2 value 810.565721
#> iter 3 value 796.559650
#> iter 4 value 794.769234
#> iter 5 value 758.876864
#> iter 6 value 750.342003
#> iter 7 value 749.063438
#> iter 8 value 749.038146
#> iter 9 value 749.038114
#> iter 9 value 749.038104
#> iter 9 value 749.038098
#> final value 749.038098
#> converged
#> This is Run number 160
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.1534838 0.1509388 -0.7034838 -12.449061 1
#> 2 1 -0.95 -2.35 -0.7931639 -1.1335804 -1.7431639 -3.483580 1
#> 3 1 -6.20 -2.30 0.1991533 -0.9363168 -6.0008467 -3.236317 2
#> 4 1 -13.90 -2.55 0.1736630 0.5310906 -13.7263370 -2.018909 2
#> 5 1 -14.40 -5.80 0.9010981 0.2076687 -13.4989019 -5.592331 2
#> 6 1 -3.60 -1.70 0.4056225 -0.4256635 -3.1943775 -2.125664 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -40200 6725
#> initial value 998.131940
#> iter 2 value 792.504082
#> iter 3 value 779.511942
#> iter 4 value 777.665254
#> iter 5 value 745.791488
#> iter 6 value 737.045892
#> iter 7 value 735.750623
#> iter 8 value 735.720557
#> iter 9 value 735.720510
#> iter 9 value 735.720509
#> iter 9 value 735.720509
#> final value 735.720509
#> converged
#> This is Run number 161
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.8941682 -0.09420352 3.3441682 -12.6942035 1
#> 2 1 -0.95 -2.35 0.4358084 -0.64355644 -0.5141916 -2.9935564 1
#> 3 1 -6.20 -2.30 0.8005120 1.02216237 -5.3994880 -1.2778376 2
#> 4 1 -13.90 -2.55 1.1187836 1.30594143 -12.7812164 -1.2440586 2
#> 5 1 -14.40 -5.80 1.9581834 -0.51155744 -12.4418166 -6.3115574 2
#> 6 1 -3.60 -1.70 -0.1522272 0.90016952 -3.7522272 -0.7998305 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -39575 6800
#> initial value 998.131940
#> iter 2 value 802.223079
#> iter 3 value 787.609132
#> iter 4 value 784.579141
#> iter 5 value 751.191393
#> iter 6 value 742.524072
#> iter 7 value 741.233800
#> iter 8 value 741.205637
#> iter 9 value 741.205597
#> iter 9 value 741.205590
#> iter 9 value 741.205585
#> final value 741.205585
#> converged
#> This is Run number 162
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4024772 2.2065009 -0.1475228 -10.393499 1
#> 2 1 -0.95 -2.35 1.9501775 -0.6720595 1.0001775 -3.022059 1
#> 3 1 -6.20 -2.30 2.4944470 1.1268340 -3.7055530 -1.173166 2
#> 4 1 -13.90 -2.55 1.0818204 -0.3008397 -12.8181796 -2.850840 2
#> 5 1 -14.40 -5.80 0.3670193 0.7052709 -14.0329807 -5.094729 2
#> 6 1 -3.60 -1.70 0.7669320 0.5907449 -2.8330680 -1.109255 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38400 6425
#> initial value 998.131940
#> iter 2 value 821.459643
#> iter 3 value 811.235144
#> iter 4 value 809.808167
#> iter 5 value 772.414800
#> iter 6 value 763.932312
#> iter 7 value 762.433650
#> iter 8 value 762.399186
#> iter 9 value 762.399114
#> iter 9 value 762.399113
#> iter 9 value 762.399113
#> final value 762.399113
#> converged
#> This is Run number 163
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8459106 0.2562057 -1.3959106 -12.34379426 1
#> 2 1 -0.95 -2.35 1.8055598 -0.2288344 0.8555598 -2.57883441 1
#> 3 1 -6.20 -2.30 1.8646730 2.2020751 -4.3353270 -0.09792495 2
#> 4 1 -13.90 -2.55 0.8799374 -0.5573151 -13.0200626 -3.10731515 2
#> 5 1 -14.40 -5.80 4.7217307 0.2221229 -9.6782693 -5.57787711 2
#> 6 1 -3.60 -1.70 0.4361255 -0.8619898 -3.1638745 -2.56198977 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39225 7050
#> initial value 998.131940
#> iter 2 value 805.972527
#> iter 3 value 793.127502
#> iter 4 value 791.702106
#> iter 5 value 756.829082
#> iter 6 value 748.203899
#> iter 7 value 746.884422
#> iter 8 value 746.856053
#> iter 9 value 746.856009
#> iter 10 value 746.855998
#> iter 10 value 746.855989
#> iter 10 value 746.855983
#> final value 746.855983
#> converged
#> This is Run number 164
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.35174017 -0.2326349 0.8017402 -12.8326349 1
#> 2 1 -0.95 -2.35 0.04486872 0.4759409 -0.9051313 -1.8740591 1
#> 3 1 -6.20 -2.30 0.76992536 0.3174228 -5.4300746 -1.9825772 2
#> 4 1 -13.90 -2.55 -0.60627405 1.6330446 -14.5062740 -0.9169554 2
#> 5 1 -14.40 -5.80 -1.34156099 -0.7300498 -15.7415610 -6.5300498 2
#> 6 1 -3.60 -1.70 4.19109845 -0.5847035 0.5910984 -2.2847035 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7340 -40925 6625
#> initial value 998.131940
#> iter 2 value 780.605962
#> iter 3 value 769.056220
#> iter 4 value 768.294039
#> iter 5 value 738.250872
#> iter 6 value 729.435459
#> iter 7 value 728.148023
#> iter 8 value 728.116321
#> iter 9 value 728.116266
#> iter 10 value 728.116255
#> iter 10 value 728.116248
#> iter 10 value 728.116241
#> final value 728.116241
#> converged
#> This is Run number 165
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.4828286 -0.77702401 0.9328286 -13.377024 1
#> 2 1 -0.95 -2.35 -0.1076765 0.28578178 -1.0576765 -2.064218 1
#> 3 1 -6.20 -2.30 1.5515890 -1.37701768 -4.6484110 -3.677018 2
#> 4 1 -13.90 -2.55 0.7053390 0.04244316 -13.1946610 -2.507557 2
#> 5 1 -14.40 -5.80 -0.3282014 4.34726022 -14.7282014 -1.452740 2
#> 6 1 -3.60 -1.70 1.5438018 -0.65594209 -2.0561982 -2.355942 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6600 -39450 7250
#> initial value 998.131940
#> iter 2 value 801.327289
#> iter 3 value 788.069927
#> iter 4 value 786.986615
#> iter 5 value 752.732022
#> iter 6 value 744.083323
#> iter 7 value 742.808823
#> iter 8 value 742.782266
#> iter 9 value 742.782229
#> iter 10 value 742.782218
#> iter 10 value 742.782208
#> iter 10 value 742.782202
#> final value 742.782202
#> converged
#> This is Run number 166
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.2470518 -1.5662488 2.6970518 -14.166249 1
#> 2 1 -0.95 -2.35 1.5102476 0.5018118 0.5602476 -1.848188 1
#> 3 1 -6.20 -2.30 0.7285373 -0.9111377 -5.4714627 -3.211138 2
#> 4 1 -13.90 -2.55 1.0032664 0.5799024 -12.8967336 -1.970098 2
#> 5 1 -14.40 -5.80 -1.0072278 2.3951188 -15.4072278 -3.404881 2
#> 6 1 -3.60 -1.70 -0.5007747 -0.1459498 -4.1007747 -1.845950 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37850 6450
#> initial value 998.131940
#> iter 2 value 829.396853
#> iter 3 value 818.195621
#> iter 4 value 815.979070
#> iter 5 value 777.273101
#> iter 6 value 768.912330
#> iter 7 value 767.450212
#> iter 8 value 767.418620
#> iter 9 value 767.418560
#> iter 9 value 767.418550
#> iter 9 value 767.418544
#> final value 767.418544
#> converged
#> This is Run number 167
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 6.210010956 0.9690609 5.6600110 -11.6309391 1
#> 2 1 -0.95 -2.35 0.128578778 1.5716314 -0.8214212 -0.7783686 2
#> 3 1 -6.20 -2.30 4.427367559 -0.7495352 -1.7726324 -3.0495352 1
#> 4 1 -13.90 -2.55 -0.432867145 0.8710364 -14.3328671 -1.6789636 2
#> 5 1 -14.40 -5.80 0.002340605 0.9181577 -14.3976594 -4.8818423 2
#> 6 1 -3.60 -1.70 -0.442111183 -0.2147327 -4.0421112 -1.9147327 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38350 7200
#> initial value 998.131940
#> iter 2 value 818.137327
#> iter 3 value 805.799048
#> iter 4 value 804.553795
#> iter 5 value 767.069334
#> iter 6 value 758.599634
#> iter 7 value 757.260562
#> iter 8 value 757.233309
#> iter 9 value 757.233267
#> iter 10 value 757.233254
#> iter 10 value 757.233244
#> iter 10 value 757.233238
#> final value 757.233238
#> converged
#> This is Run number 168
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.16828034 -0.19179388 -0.7182803 -12.791794 1
#> 2 1 -0.95 -2.35 -0.01768426 -0.95595519 -0.9676843 -3.305955 1
#> 3 1 -6.20 -2.30 1.07361811 0.12428209 -5.1263819 -2.175718 2
#> 4 1 -13.90 -2.55 -1.48609969 0.04991446 -15.3860997 -2.500086 2
#> 5 1 -14.40 -5.80 0.56137385 3.00713266 -13.8386262 -2.792867 2
#> 6 1 -3.60 -1.70 0.51907780 -0.28979636 -3.0809222 -1.989796 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5800 -36425 6625
#> initial value 998.131940
#> iter 2 value 847.707465
#> iter 3 value 838.185997
#> iter 4 value 836.660612
#> iter 5 value 793.887708
#> iter 6 value 785.953742
#> iter 7 value 784.537768
#> iter 8 value 784.510629
#> iter 9 value 784.510581
#> iter 9 value 784.510578
#> iter 9 value 784.510578
#> final value 784.510578
#> converged
#> This is Run number 169
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 4.4480199 -0.75530324 3.8980199 -13.3553032 1
#> 2 1 -0.95 -2.35 0.8271159 1.36319291 -0.1228841 -0.9868071 1
#> 3 1 -6.20 -2.30 2.9929490 5.74847339 -3.2070510 3.4484734 2
#> 4 1 -13.90 -2.55 -1.2897084 2.81034097 -15.1897084 0.2603410 2
#> 5 1 -14.40 -5.80 0.6008244 0.72731480 -13.7991756 -5.0726852 2
#> 6 1 -3.60 -1.70 0.5481241 -0.06931992 -3.0518759 -1.7693199 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7360 -39400 6650
#> initial value 998.131940
#> iter 2 value 804.455522
#> iter 3 value 794.918487
#> iter 4 value 794.819545
#> iter 5 value 759.968614
#> iter 6 value 751.295296
#> iter 7 value 749.801974
#> iter 8 value 749.764962
#> iter 9 value 749.764873
#> iter 10 value 749.764854
#> iter 10 value 749.764846
#> iter 10 value 749.764837
#> final value 749.764837
#> converged
#> This is Run number 170
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.18507888 0.16385218 -0.3649211 -12.436148 1
#> 2 1 -0.95 -2.35 0.39011929 0.91902517 -0.5598807 -1.430975 1
#> 3 1 -6.20 -2.30 0.21859640 -0.55904567 -5.9814036 -2.859046 2
#> 4 1 -13.90 -2.55 -1.12228819 -0.38246311 -15.0222882 -2.932463 2
#> 5 1 -14.40 -5.80 0.07611045 1.03420648 -14.3238895 -4.765794 2
#> 6 1 -3.60 -1.70 0.29273584 0.03752286 -3.3072642 -1.662477 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38725 6925
#> initial value 998.131940
#> iter 2 value 814.132713
#> iter 3 value 802.258990
#> iter 4 value 800.931184
#> iter 5 value 764.520624
#> iter 6 value 755.970302
#> iter 7 value 754.592956
#> iter 8 value 754.563019
#> iter 9 value 754.562967
#> iter 10 value 754.562955
#> iter 10 value 754.562945
#> iter 10 value 754.562945
#> final value 754.562945
#> converged
#> This is Run number 171
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.38130658 1.0115170 -0.1686934 -11.588483 1
#> 2 1 -0.95 -2.35 0.01982722 1.2410011 -0.9301728 -1.108999 1
#> 3 1 -6.20 -2.30 0.77813010 -0.7520586 -5.4218699 -3.052059 2
#> 4 1 -13.90 -2.55 0.49137246 -0.7456776 -13.4086275 -3.295678 2
#> 5 1 -14.40 -5.80 1.00506794 -0.6362403 -13.3949321 -6.436240 2
#> 6 1 -3.60 -1.70 -0.91253799 0.1935483 -4.5125380 -1.506452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -40575 6875
#> initial value 998.131940
#> iter 2 value 785.566447
#> iter 3 value 772.155593
#> iter 4 value 770.588870
#> iter 5 value 739.805612
#> iter 6 value 731.052874
#> iter 7 value 729.821595
#> iter 8 value 729.793782
#> iter 9 value 729.793744
#> iter 9 value 729.793735
#> iter 9 value 729.793729
#> final value 729.793729
#> converged
#> This is Run number 172
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4409470 -0.7932469 -0.99094698 -13.393247 1
#> 2 1 -0.95 -2.35 0.9145395 -0.3289082 -0.03546045 -2.678908 1
#> 3 1 -6.20 -2.30 1.1574568 -0.7803319 -5.04254318 -3.080332 2
#> 4 1 -13.90 -2.55 -0.6775352 -0.5768270 -14.57753519 -3.126827 2
#> 5 1 -14.40 -5.80 0.7977654 -0.2551995 -13.60223459 -6.055199 2
#> 6 1 -3.60 -1.70 -1.0778157 0.3826733 -4.67781574 -1.317327 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39625 6850
#> initial value 998.131940
#> iter 2 value 801.282254
#> iter 3 value 784.716401
#> iter 4 value 780.606245
#> iter 5 value 747.641999
#> iter 6 value 738.977177
#> iter 7 value 737.740404
#> iter 8 value 737.714532
#> iter 9 value 737.714500
#> iter 9 value 737.714494
#> iter 9 value 737.714490
#> final value 737.714490
#> converged
#> This is Run number 173
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.421346074 0.4893955 0.8713461 -12.1106045 1
#> 2 1 -0.95 -2.35 2.216092730 3.1490119 1.2660927 0.7990119 1
#> 3 1 -6.20 -2.30 1.900551535 1.4918179 -4.2994485 -0.8081821 2
#> 4 1 -13.90 -2.55 1.063080893 1.1520007 -12.8369191 -1.3979993 2
#> 5 1 -14.40 -5.80 -0.003249443 1.4609062 -14.4032494 -4.3390938 2
#> 6 1 -3.60 -1.70 1.932355926 0.7714596 -1.6676441 -0.9285404 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37375 6250
#> initial value 998.131940
#> iter 2 value 836.943545
#> iter 3 value 826.925249
#> iter 4 value 824.938504
#> iter 5 value 784.846526
#> iter 6 value 776.624489
#> iter 7 value 775.116530
#> iter 8 value 775.084256
#> iter 9 value 775.084190
#> iter 9 value 775.084180
#> iter 9 value 775.084175
#> final value 775.084175
#> converged
#> This is Run number 174
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.31013417 -0.2115279 -0.8601342 -12.8115279 1
#> 2 1 -0.95 -2.35 -0.53787463 -0.3893213 -1.4878746 -2.7393213 1
#> 3 1 -6.20 -2.30 0.04893292 -0.3078683 -6.1510671 -2.6078683 2
#> 4 1 -13.90 -2.55 -0.28150001 1.6459548 -14.1815000 -0.9040452 2
#> 5 1 -14.40 -5.80 1.56821981 1.8214466 -12.8317802 -3.9785534 2
#> 6 1 -3.60 -1.70 -0.35828502 2.0678416 -3.9582850 0.3678416 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -39400 7425
#> initial value 998.131940
#> iter 2 value 801.411006
#> iter 3 value 785.492116
#> iter 4 value 782.999205
#> iter 5 value 749.073145
#> iter 6 value 740.496753
#> iter 7 value 739.288779
#> iter 8 value 739.265701
#> iter 9 value 739.265679
#> iter 9 value 739.265672
#> iter 9 value 739.265666
#> final value 739.265666
#> converged
#> This is Run number 175
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8872974 0.12341300 0.3372974 -12.4765870 1
#> 2 1 -0.95 -2.35 1.6189959 1.68494407 0.6689959 -0.6650559 1
#> 3 1 -6.20 -2.30 1.8328573 -0.34986021 -4.3671427 -2.6498602 2
#> 4 1 -13.90 -2.55 0.3975676 -0.46245576 -13.5024324 -3.0124558 2
#> 5 1 -14.40 -5.80 0.3211577 -0.06038181 -14.0788423 -5.8603818 2
#> 6 1 -3.60 -1.70 -1.0312273 -1.01319438 -4.6312273 -2.7131944 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -37425 8125
#> initial value 998.131940
#> iter 2 value 825.669270
#> iter 3 value 811.266908
#> iter 4 value 809.984140
#> iter 5 value 769.899215
#> iter 6 value 761.667549
#> iter 7 value 760.451298
#> iter 8 value 760.432272
#> iter 9 value 760.432257
#> iter 9 value 760.432255
#> iter 10 value 760.432241
#> iter 10 value 760.432231
#> iter 10 value 760.432231
#> final value 760.432231
#> converged
#> This is Run number 176
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.3745435 -0.29377364 2.8245435 -12.893774 1
#> 2 1 -0.95 -2.35 -0.5793627 0.32469731 -1.5293627 -2.025303 1
#> 3 1 -6.20 -2.30 -0.8267588 -1.55561020 -7.0267588 -3.855610 2
#> 4 1 -13.90 -2.55 1.1583074 -0.05119815 -12.7416926 -2.601198 2
#> 5 1 -14.40 -5.80 0.9096218 0.31094409 -13.4903782 -5.489056 2
#> 6 1 -3.60 -1.70 3.2312005 -0.13720072 -0.3687995 -1.837201 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -40275 7050
#> initial value 998.131940
#> iter 2 value 789.275549
#> iter 3 value 776.363160
#> iter 4 value 775.464621
#> iter 5 value 743.600302
#> iter 6 value 734.854965
#> iter 7 value 733.603681
#> iter 8 value 733.576007
#> iter 9 value 733.575967
#> iter 10 value 733.575956
#> iter 10 value 733.575947
#> iter 10 value 733.575940
#> final value 733.575940
#> converged
#> This is Run number 177
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.174721419 0.2918176 1.6247214 -12.3081824 1
#> 2 1 -0.95 -2.35 1.541069712 0.4410086 0.5910697 -1.9089914 1
#> 3 1 -6.20 -2.30 -1.090772027 1.9146486 -7.2907720 -0.3853514 2
#> 4 1 -13.90 -2.55 0.377090608 -0.9893143 -13.5229094 -3.5393143 2
#> 5 1 -14.40 -5.80 -0.919079935 -0.7391974 -15.3190799 -6.5391974 2
#> 6 1 -3.60 -1.70 0.001740311 1.1685960 -3.5982597 -0.5314040 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38825 6750
#> initial value 998.131940
#> iter 2 value 813.643151
#> iter 3 value 801.736130
#> iter 4 value 800.051369
#> iter 5 value 764.017687
#> iter 6 value 755.447785
#> iter 7 value 754.051034
#> iter 8 value 754.019933
#> iter 9 value 754.019878
#> iter 10 value 754.019866
#> iter 10 value 754.019858
#> iter 10 value 754.019857
#> final value 754.019857
#> converged
#> This is Run number 178
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.157130763 2.14610729 -0.7071308 -10.4538927 1
#> 2 1 -0.95 -2.35 -1.577677435 0.07339648 -2.5276774 -2.2766035 2
#> 3 1 -6.20 -2.30 -0.003356045 -0.17701049 -6.2033560 -2.4770105 2
#> 4 1 -13.90 -2.55 1.337153663 -0.22073210 -12.5628463 -2.7707321 2
#> 5 1 -14.40 -5.80 1.206183765 -0.88403495 -13.1938162 -6.6840350 2
#> 6 1 -3.60 -1.70 1.164644577 2.39105834 -2.4353554 0.6910583 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -39225 7500
#> initial value 998.131940
#> iter 2 value 803.573969
#> iter 3 value 788.306160
#> iter 4 value 786.339931
#> iter 5 value 751.742337
#> iter 6 value 743.178570
#> iter 7 value 741.958460
#> iter 8 value 741.935311
#> iter 9 value 741.935288
#> iter 9 value 741.935279
#> iter 9 value 741.935273
#> final value 741.935273
#> converged
#> This is Run number 179
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.36614924 0.3678008 -1.916149 -12.232199 1
#> 2 1 -0.95 -2.35 -0.09774777 0.4061983 -1.047748 -1.943802 1
#> 3 1 -6.20 -2.30 -1.38289196 0.1333675 -7.582892 -2.166633 2
#> 4 1 -13.90 -2.55 -0.60933313 -0.3739232 -14.509333 -2.923923 2
#> 5 1 -14.40 -5.80 1.08012001 2.0695022 -13.319880 -3.730498 2
#> 6 1 -3.60 -1.70 1.76909512 -0.6888554 -1.830905 -2.388855 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5380 -38450 8225
#> initial value 998.131940
#> iter 2 value 810.608798
#> iter 3 value 791.580833
#> iter 4 value 788.319662
#> iter 5 value 751.898298
#> iter 6 value 743.572566
#> iter 7 value 742.413209
#> iter 8 value 742.395716
#> iter 8 value 742.395707
#> final value 742.395707
#> converged
#> This is Run number 180
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.42984402 1.15624238 -1.979844 -11.4437576 1
#> 2 1 -0.95 -2.35 0.47558499 1.25333024 -0.474415 -1.0966698 1
#> 3 1 -6.20 -2.30 0.92039109 0.23790478 -5.279609 -2.0620952 2
#> 4 1 -13.90 -2.55 0.11262462 3.27760830 -13.787375 0.7276083 2
#> 5 1 -14.40 -5.80 -0.08676749 0.61826096 -14.486767 -5.1817390 2
#> 6 1 -3.60 -1.70 0.63872769 0.04009302 -2.961272 -1.6599070 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -37675 7550
#> initial value 998.131940
#> iter 2 value 825.792327
#> iter 3 value 812.538935
#> iter 4 value 810.995136
#> iter 5 value 771.683888
#> iter 6 value 763.380591
#> iter 7 value 762.092411
#> iter 8 value 762.069000
#> iter 9 value 762.068970
#> iter 9 value 762.068959
#> iter 9 value 762.068953
#> final value 762.068953
#> converged
#> This is Run number 181
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5501851 -1.44881516 1.851489e-04 -14.048815 1
#> 2 1 -0.95 -2.35 -0.9403997 2.01401200 -1.890400e+00 -0.335988 2
#> 3 1 -6.20 -2.30 3.2561479 0.02313325 -2.943852e+00 -2.276867 2
#> 4 1 -13.90 -2.55 -0.6795747 0.93851184 -1.457957e+01 -1.611488 2
#> 5 1 -14.40 -5.80 3.2273245 2.75636301 -1.117268e+01 -3.043637 2
#> 6 1 -3.60 -1.70 1.3287723 0.62510498 -2.271228e+00 -1.074895 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37525 7050
#> initial value 998.131940
#> iter 2 value 830.623869
#> iter 3 value 819.786132
#> iter 4 value 818.726984
#> iter 5 value 778.803378
#> iter 6 value 770.524132
#> iter 7 value 769.135738
#> iter 8 value 769.107769
#> iter 9 value 769.107721
#> iter 10 value 769.107707
#> iter 10 value 769.107696
#> iter 10 value 769.107692
#> final value 769.107692
#> converged
#> This is Run number 182
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3877798 1.5985972 0.8377798 -11.0014028 1
#> 2 1 -0.95 -2.35 -0.7188988 -0.9631932 -1.6688988 -3.3131932 1
#> 3 1 -6.20 -2.30 0.9125603 -0.1913886 -5.2874397 -2.4913886 2
#> 4 1 -13.90 -2.55 2.4980210 -1.3445891 -11.4019790 -3.8945891 2
#> 5 1 -14.40 -5.80 -1.2407653 0.8945358 -15.6407653 -4.9054642 2
#> 6 1 -3.60 -1.70 2.6447546 1.3720081 -0.9552454 -0.3279919 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -39350 7025
#> initial value 998.131940
#> iter 2 value 804.029515
#> iter 3 value 791.861529
#> iter 4 value 790.907386
#> iter 5 value 756.253960
#> iter 6 value 747.596710
#> iter 7 value 746.261089
#> iter 8 value 746.231653
#> iter 9 value 746.231605
#> iter 10 value 746.231591
#> iter 10 value 746.231582
#> iter 10 value 746.231575
#> final value 746.231575
#> converged
#> This is Run number 183
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.80651529 -0.8156940 0.2565153 -13.415694 1
#> 2 1 -0.95 -2.35 -0.06376154 0.9184796 -1.0137615 -1.431520 1
#> 3 1 -6.20 -2.30 -0.16201991 0.3479954 -6.3620199 -1.952005 2
#> 4 1 -13.90 -2.55 -0.34846009 0.1217536 -14.2484601 -2.428246 2
#> 5 1 -14.40 -5.80 -0.63207541 -0.3123931 -15.0320754 -6.112393 2
#> 6 1 -3.60 -1.70 1.88403816 2.0195630 -1.7159618 0.319563 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37550 6825
#> initial value 998.131940
#> iter 2 value 831.441654
#> iter 3 value 821.382124
#> iter 4 value 820.418177
#> iter 5 value 780.517258
#> iter 6 value 772.236743
#> iter 7 value 770.800043
#> iter 8 value 770.769984
#> iter 9 value 770.769926
#> iter 10 value 770.769912
#> iter 10 value 770.769902
#> iter 10 value 770.769895
#> final value 770.769895
#> converged
#> This is Run number 184
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5336898 0.01430224 -1.0836898 -12.585698 1
#> 2 1 -0.95 -2.35 0.5064921 -0.80267268 -0.4435079 -3.152673 1
#> 3 1 -6.20 -2.30 0.7161820 0.93388315 -5.4838180 -1.366117 2
#> 4 1 -13.90 -2.55 1.8915819 -0.08514197 -12.0084181 -2.635142 2
#> 5 1 -14.40 -5.80 6.7373003 0.54983778 -7.6626997 -5.250162 2
#> 6 1 -3.60 -1.70 -0.7919913 -0.13593672 -4.3919913 -1.835937 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -39750 6125
#> initial value 998.131940
#> iter 2 value 802.582106
#> iter 3 value 791.516142
#> iter 4 value 789.415144
#> iter 5 value 756.164762
#> iter 6 value 747.435155
#> iter 7 value 745.952436
#> iter 8 value 745.914516
#> iter 9 value 745.914429
#> iter 9 value 745.914418
#> iter 9 value 745.914411
#> final value 745.914411
#> converged
#> This is Run number 185
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.15265139 2.2761791 0.6026514 -10.32382089 1
#> 2 1 -0.95 -2.35 -0.30652863 -0.3118787 -1.2565286 -2.66187870 1
#> 3 1 -6.20 -2.30 -0.41694314 1.1836174 -6.6169431 -1.11638259 2
#> 4 1 -13.90 -2.55 0.41632608 2.6217143 -13.4836739 0.07171428 2
#> 5 1 -14.40 -5.80 -0.03841894 1.2841927 -14.4384189 -4.51580730 2
#> 6 1 -3.60 -1.70 -0.50718130 -0.5421385 -4.1071813 -2.24213851 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -37575 6500
#> initial value 998.131940
#> iter 2 value 832.782799
#> iter 3 value 823.351503
#> iter 4 value 822.216163
#> iter 5 value 782.414388
#> iter 6 value 774.140895
#> iter 7 value 772.643795
#> iter 8 value 772.611360
#> iter 9 value 772.611293
#> iter 9 value 772.611291
#> iter 9 value 772.611291
#> final value 772.611291
#> converged
#> This is Run number 186
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.31849409 -1.1475188 -0.2315059 -13.7475188 1
#> 2 1 -0.95 -2.35 -0.22081305 1.6985502 -1.1708130 -0.6514498 2
#> 3 1 -6.20 -2.30 0.05877666 0.1210087 -6.1412233 -2.1789913 2
#> 4 1 -13.90 -2.55 0.40693132 -0.3927151 -13.4930687 -2.9427151 2
#> 5 1 -14.40 -5.80 0.83378602 0.9974509 -13.5662140 -4.8025491 2
#> 6 1 -3.60 -1.70 2.03295389 0.9473908 -1.5670461 -0.7526092 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -37500 6275
#> initial value 998.131940
#> iter 2 value 834.726166
#> iter 3 value 826.636796
#> iter 4 value 825.947470
#> iter 5 value 785.782981
#> iter 6 value 777.551282
#> iter 7 value 775.976183
#> iter 8 value 775.941005
#> iter 9 value 775.940921
#> iter 9 value 775.940919
#> iter 9 value 775.940919
#> final value 775.940919
#> converged
#> This is Run number 187
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1768436 -0.4033544 0.6268436 -13.0033544 1
#> 2 1 -0.95 -2.35 1.7434304 3.3584012 0.7934304 1.0084012 2
#> 3 1 -6.20 -2.30 0.4410919 -0.9225754 -5.7589081 -3.2225754 2
#> 4 1 -13.90 -2.55 0.9139621 -0.4707154 -12.9860379 -3.0207154 2
#> 5 1 -14.40 -5.80 1.8159705 -0.3670249 -12.5840295 -6.1670249 2
#> 6 1 -3.60 -1.70 -0.1686814 2.1369949 -3.7686814 0.4369949 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37975 6525
#> initial value 998.131940
#> iter 2 value 827.122648
#> iter 3 value 816.774891
#> iter 4 value 815.272899
#> iter 5 value 776.706030
#> iter 6 value 768.322593
#> iter 7 value 766.846473
#> iter 8 value 766.813985
#> iter 9 value 766.813920
#> iter 9 value 766.813920
#> iter 9 value 766.813920
#> final value 766.813920
#> converged
#> This is Run number 188
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.0338425 0.8205150 1.483843 -11.7794850 1
#> 2 1 -0.95 -2.35 -0.8180443 -0.8602384 -1.768044 -3.2102384 1
#> 3 1 -6.20 -2.30 0.6849739 -0.3229602 -5.515026 -2.6229602 2
#> 4 1 -13.90 -2.55 0.3239195 1.8556292 -13.576080 -0.6943708 2
#> 5 1 -14.40 -5.80 -0.7300829 -0.2151003 -15.130083 -6.0151003 2
#> 6 1 -3.60 -1.70 1.4884202 -0.5213997 -2.111580 -2.2213997 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5840 -36775 6075
#> initial value 998.131940
#> iter 2 value 845.878251
#> iter 3 value 836.328672
#> iter 4 value 834.205564
#> iter 5 value 792.548050
#> iter 6 value 784.507969
#> iter 7 value 782.994471
#> iter 8 value 782.963394
#> iter 9 value 782.963331
#> iter 9 value 782.963321
#> iter 9 value 782.963317
#> final value 782.963317
#> converged
#> This is Run number 189
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.4316206 2.0186043 -0.9816206 -10.581396 1
#> 2 1 -0.95 -2.35 -0.9205920 0.9624501 -1.8705920 -1.387550 2
#> 3 1 -6.20 -2.30 -1.0869945 0.3877159 -7.2869945 -1.912284 2
#> 4 1 -13.90 -2.55 2.7058583 1.2630219 -11.1941417 -1.286978 2
#> 5 1 -14.40 -5.80 -0.1632859 -0.3171861 -14.5632859 -6.117186 2
#> 6 1 -3.60 -1.70 0.7129282 0.3385117 -2.8870718 -1.361488 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6500 -38400 6275
#> initial value 998.131940
#> iter 2 value 822.177848
#> iter 3 value 812.347784
#> iter 4 value 810.892362
#> iter 5 value 773.494169
#> iter 6 value 765.015975
#> iter 7 value 763.480907
#> iter 8 value 763.444953
#> iter 9 value 763.444873
#> iter 10 value 763.444861
#> iter 10 value 763.444854
#> iter 10 value 763.444851
#> final value 763.444851
#> converged
#> This is Run number 190
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8669391 1.2829662 0.3169391 -11.3170338 1
#> 2 1 -0.95 -2.35 -0.4963417 1.0327632 -1.4463417 -1.3172368 2
#> 3 1 -6.20 -2.30 -0.1639651 2.4129229 -6.3639651 0.1129229 2
#> 4 1 -13.90 -2.55 2.1850226 -0.4910186 -11.7149774 -3.0410186 2
#> 5 1 -14.40 -5.80 0.4407121 0.6021247 -13.9592879 -5.1978753 2
#> 6 1 -3.60 -1.70 1.5326628 2.8870041 -2.0673372 1.1870041 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7420 -40625 4875
#> initial value 998.131940
#> iter 2 value 793.259227
#> iter 3 value 785.481207
#> iter 4 value 783.382954
#> iter 5 value 752.757599
#> iter 6 value 744.010708
#> iter 7 value 742.141658
#> iter 8 value 742.079824
#> iter 9 value 742.079515
#> iter 10 value 742.079487
#> iter 10 value 742.079486
#> iter 11 value 742.079468
#> iter 11 value 742.079462
#> iter 11 value 742.079459
#> final value 742.079459
#> converged
#> This is Run number 191
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.04740747 -0.21692241 -0.5974075 -12.81692241 1
#> 2 1 -0.95 -2.35 1.50952731 -0.55648315 0.5595273 -2.90648315 1
#> 3 1 -6.20 -2.30 0.59228059 -0.18472714 -5.6077194 -2.48472714 2
#> 4 1 -13.90 -2.55 0.69356433 0.02821362 -13.2064357 -2.52178638 2
#> 5 1 -14.40 -5.80 -0.15262047 1.87286297 -14.5526205 -3.92713703 2
#> 6 1 -3.60 -1.70 0.38306370 1.61245394 -3.2169363 -0.08754606 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -38250 6925
#> initial value 998.131940
#> iter 2 value 821.246532
#> iter 3 value 808.446353
#> iter 4 value 806.263232
#> iter 5 value 768.732781
#> iter 6 value 760.285536
#> iter 7 value 758.922635
#> iter 8 value 758.894445
#> iter 9 value 758.894402
#> iter 9 value 758.894392
#> iter 9 value 758.894386
#> final value 758.894386
#> converged
#> This is Run number 192
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.77438849 0.3426618 2.224388 -12.257338 1
#> 2 1 -0.95 -2.35 3.31776593 0.4104071 2.367766 -1.939593 1
#> 3 1 -6.20 -2.30 -0.01538850 -1.3005204 -6.215388 -3.600520 2
#> 4 1 -13.90 -2.55 0.05183684 -1.0913297 -13.848163 -3.641330 2
#> 5 1 -14.40 -5.80 -0.54034107 0.2902806 -14.940341 -5.509719 2
#> 6 1 -3.60 -1.70 1.39107077 -0.6858458 -2.208929 -2.385846 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6440 -38950 5975
#> initial value 998.131940
#> iter 2 value 815.636264
#> iter 3 value 804.901308
#> iter 4 value 802.500386
#> iter 5 value 766.969640
#> iter 6 value 758.365476
#> iter 7 value 756.809996
#> iter 8 value 756.771283
#> iter 9 value 756.771187
#> iter 10 value 756.771175
#> iter 10 value 756.771175
#> iter 10 value 756.771170
#> final value 756.771170
#> converged
#> This is Run number 193
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.23681938 4.23561905 1.6868194 -8.364381 1
#> 2 1 -0.95 -2.35 0.62215365 -0.08347456 -0.3278463 -2.433475 1
#> 3 1 -6.20 -2.30 3.33367967 -0.82596626 -2.8663203 -3.125966 1
#> 4 1 -13.90 -2.55 -0.60050490 1.25185987 -14.5005049 -1.298140 2
#> 5 1 -14.40 -5.80 -1.04581477 -0.79087053 -15.4458148 -6.590871 2
#> 6 1 -3.60 -1.70 0.04483899 -0.13272195 -3.5551610 -1.832722 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -38450 6875
#> initial value 998.131940
#> iter 2 value 818.718002
#> iter 3 value 803.697893
#> iter 4 value 800.168359
#> iter 5 value 763.562357
#> iter 6 value 755.061158
#> iter 7 value 753.740804
#> iter 8 value 753.714085
#> iter 9 value 753.714049
#> iter 9 value 753.714041
#> iter 9 value 753.714036
#> final value 753.714036
#> converged
#> This is Run number 194
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2685430 -0.4870776 -0.8185430 -13.087078 1
#> 2 1 -0.95 -2.35 0.8251384 0.2982941 -0.1248616 -2.051706 1
#> 3 1 -6.20 -2.30 -0.4028685 0.1790501 -6.6028685 -2.120950 2
#> 4 1 -13.90 -2.55 0.2935466 -1.3087466 -13.6064534 -3.858747 2
#> 5 1 -14.40 -5.80 0.5960075 2.7431325 -13.8039925 -3.056868 2
#> 6 1 -3.60 -1.70 0.5781135 1.4689670 -3.0218865 -0.231033 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6960 -41000 6825
#> initial value 998.131940
#> iter 2 value 778.809209
#> iter 3 value 765.158628
#> iter 4 value 763.484505
#> iter 5 value 734.027050
#> iter 6 value 725.271131
#> iter 7 value 724.083866
#> iter 8 value 724.056948
#> iter 9 value 724.056913
#> iter 9 value 724.056912
#> iter 9 value 724.056912
#> final value 724.056912
#> converged
#> This is Run number 195
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8492848 -0.53395365 2.2992848 -13.1339536 1
#> 2 1 -0.95 -2.35 0.3839092 1.63353669 -0.5660908 -0.7164633 1
#> 3 1 -6.20 -2.30 -0.5999922 -0.02843212 -6.7999922 -2.3284321 2
#> 4 1 -13.90 -2.55 -0.1481716 -1.16700661 -14.0481716 -3.7170066 2
#> 5 1 -14.40 -5.80 -0.1826396 0.62942178 -14.5826396 -5.1705782 2
#> 6 1 -3.60 -1.70 -0.3461750 0.92165860 -3.9461750 -0.7783414 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6920 -38300 7675
#> initial value 998.131940
#> iter 2 value 815.378508
#> iter 3 value 803.595570
#> iter 4 value 803.587425
#> iter 5 value 765.383725
#> iter 6 value 757.202761
#> iter 7 value 755.994848
#> iter 8 value 755.973212
#> iter 9 value 755.973177
#> iter 9 value 755.973170
#> iter 9 value 755.973160
#> final value 755.973160
#> converged
#> This is Run number 196
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2584187 1.27538370 -0.2915813 -11.3246163 1
#> 2 1 -0.95 -2.35 -1.1944636 1.60267970 -2.1444636 -0.7473203 2
#> 3 1 -6.20 -2.30 0.3963088 0.04613938 -5.8036912 -2.2538606 2
#> 4 1 -13.90 -2.55 1.2945879 -1.05373477 -12.6054121 -3.6037348 2
#> 5 1 -14.40 -5.80 0.7435609 1.86424057 -13.6564391 -3.9357594 2
#> 6 1 -3.60 -1.70 -0.7769179 0.82060087 -4.3769179 -0.8793991 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6860 -40000 6125
#> initial value 998.131940
#> iter 2 value 798.553892
#> iter 3 value 787.687845
#> iter 4 value 785.804415
#> iter 5 value 753.230464
#> iter 6 value 744.470930
#> iter 7 value 742.997792
#> iter 8 value 742.959543
#> iter 9 value 742.959455
#> iter 9 value 742.959444
#> iter 9 value 742.959437
#> final value 742.959437
#> converged
#> This is Run number 197
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.1795092 0.1768442 0.6295092 -12.4231558 1
#> 2 1 -0.95 -2.35 0.4985522 2.6045716 -0.4514478 0.2545716 2
#> 3 1 -6.20 -2.30 -1.2315964 0.9454194 -7.4315964 -1.3545806 2
#> 4 1 -13.90 -2.55 -0.3435481 1.3788827 -14.2435481 -1.1711173 2
#> 5 1 -14.40 -5.80 3.7034150 -0.3254818 -10.6965850 -6.1254818 2
#> 6 1 -3.60 -1.70 2.0566962 3.7886589 -1.5433038 2.0886589 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -40725 7125
#> initial value 998.131940
#> iter 2 value 781.788472
#> iter 3 value 767.303168
#> iter 4 value 765.751687
#> iter 5 value 735.496737
#> iter 6 value 726.782344
#> iter 7 value 725.620422
#> iter 8 value 725.595971
#> iter 9 value 725.595944
#> iter 9 value 725.595937
#> iter 9 value 725.595936
#> final value 725.595936
#> converged
#> This is Run number 198
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.676615 -0.4508708 2.1266146 -13.050871 1
#> 2 1 -0.95 -2.35 1.159416 -0.5837382 0.2094159 -2.933738 1
#> 3 1 -6.20 -2.30 1.261371 -0.7553756 -4.9386295 -3.055376 2
#> 4 1 -13.90 -2.55 2.460986 -0.4025537 -11.4390143 -2.952554 2
#> 5 1 -14.40 -5.80 0.898933 2.3905539 -13.5010670 -3.409446 2
#> 6 1 -3.60 -1.70 -1.191725 0.2209825 -4.7917249 -1.479018 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -40000 7100
#> initial value 998.131940
#> iter 2 value 793.663299
#> iter 3 value 779.872106
#> iter 4 value 778.346302
#> iter 5 value 745.856404
#> iter 6 value 737.157314
#> iter 7 value 735.913605
#> iter 8 value 735.886988
#> iter 9 value 735.886953
#> iter 9 value 735.886943
#> iter 9 value 735.886936
#> final value 735.886936
#> converged
#> This is Run number 199
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5658026 0.1511926 -1.11580255 -12.4488074 1
#> 2 1 -0.95 -2.35 0.8758248 1.6622111 -0.07417522 -0.6877889 1
#> 3 1 -6.20 -2.30 -0.1747381 1.3247372 -6.37473815 -0.9752628 2
#> 4 1 -13.90 -2.55 -0.6417134 1.1229533 -14.54171342 -1.4270467 2
#> 5 1 -14.40 -5.80 1.6665734 -0.2648074 -12.73342657 -6.0648074 2
#> 6 1 -3.60 -1.70 -0.2353709 0.8166244 -3.83537086 -0.8833756 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6340 -39625 6575
#> initial value 998.131940
#> iter 2 value 802.556116
#> iter 3 value 789.091674
#> iter 4 value 786.330848
#> iter 5 value 752.974064
#> iter 6 value 744.278695
#> iter 7 value 742.933661
#> iter 8 value 742.902636
#> iter 9 value 742.902584
#> iter 9 value 742.902575
#> iter 9 value 742.902570
#> final value 742.902570
#> converged
#> This is Run number 200
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.74858405 -0.5936579 0.1985841 -13.19365786 1
#> 2 1 -0.95 -2.35 -0.50898491 0.2072589 -1.4589849 -2.14274111 1
#> 3 1 -6.20 -2.30 2.07503380 3.9442964 -4.1249662 1.64429640 2
#> 4 1 -13.90 -2.55 -0.08858795 2.1107706 -13.9885880 -0.43922944 2
#> 5 1 -14.40 -5.80 0.76113817 -0.5174640 -13.6388618 -6.31746397 2
#> 6 1 -3.60 -1.70 -0.70785248 1.7888556 -4.3078525 0.08885562 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38250 7125
#> initial value 998.131940
#> iter 2 value 820.162332
#> iter 3 value 806.641201
#> iter 4 value 804.398536
#> iter 5 value 766.912473
#> iter 6 value 758.474755
#> iter 7 value 757.149550
#> iter 8 value 757.123155
#> iter 9 value 757.123118
#> iter 9 value 757.123108
#> iter 9 value 757.123102
#> final value 757.123102
#> converged
#> This is Run number 201
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7083281 -0.23988548 -1.258328e+00 -12.839885 1
#> 2 1 -0.95 -2.35 0.9506646 -0.50004482 6.645586e-04 -2.850045 1
#> 3 1 -6.20 -2.30 -0.1447649 -0.03361594 -6.344765e+00 -2.333616 2
#> 4 1 -13.90 -2.55 5.9692551 -1.35843711 -7.930745e+00 -3.908437 2
#> 5 1 -14.40 -5.80 -0.6342011 2.02312797 -1.503420e+01 -3.776872 2
#> 6 1 -3.60 -1.70 -0.3238174 -0.69004692 -3.923817e+00 -2.390047 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6820 -39875 5950
#> initial value 998.131940
#> iter 2 value 801.375294
#> iter 3 value 790.814640
#> iter 4 value 788.724097
#> iter 5 value 755.826632
#> iter 6 value 747.081158
#> iter 7 value 745.554604
#> iter 8 value 745.514137
#> iter 9 value 745.514034
#> iter 10 value 745.514022
#> iter 10 value 745.514022
#> iter 10 value 745.514016
#> final value 745.514016
#> converged
#> This is Run number 202
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5697809 -0.7909869 0.01978094 -13.3909869 1
#> 2 1 -0.95 -2.35 2.4273928 1.6648303 1.47739277 -0.6851697 1
#> 3 1 -6.20 -2.30 1.4611589 0.3452577 -4.73884110 -1.9547423 2
#> 4 1 -13.90 -2.55 -0.8986482 0.3966028 -14.79864816 -2.1533972 2
#> 5 1 -14.40 -5.80 -1.2740867 0.3010369 -15.67408671 -5.4989631 2
#> 6 1 -3.60 -1.70 1.5582558 -1.1247511 -2.04174419 -2.8247511 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -37450 6125
#> initial value 998.131940
#> iter 2 value 836.231956
#> iter 3 value 828.120323
#> iter 4 value 827.144406
#> iter 5 value 786.934084
#> iter 6 value 778.723677
#> iter 7 value 777.133218
#> iter 8 value 777.097716
#> iter 9 value 777.097631
#> iter 9 value 777.097630
#> iter 9 value 777.097630
#> final value 777.097630
#> converged
#> This is Run number 203
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.97575981 1.77107368 -1.525760 -10.828926 1
#> 2 1 -0.95 -2.35 -0.47955729 -0.02563109 -1.429557 -2.375631 1
#> 3 1 -6.20 -2.30 -0.11500065 0.24392994 -6.315001 -2.056070 2
#> 4 1 -13.90 -2.55 -0.32306038 1.25897720 -14.223060 -1.291023 2
#> 5 1 -14.40 -5.80 0.07754566 -0.51699646 -14.322454 -6.316996 2
#> 6 1 -3.60 -1.70 -1.26012197 -0.26795801 -4.860122 -1.967958 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5540 -37525 7425
#> initial value 998.131940
#> iter 2 value 828.662301
#> iter 3 value 814.421967
#> iter 4 value 811.902972
#> iter 5 value 772.426458
#> iter 6 value 764.166167
#> iter 7 value 762.877585
#> iter 8 value 762.854421
#> iter 9 value 762.854394
#> iter 9 value 762.854384
#> iter 9 value 762.854379
#> final value 762.854379
#> converged
#> This is Run number 204
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.82756837 0.9945737 2.2775684 -11.605426 1
#> 2 1 -0.95 -2.35 0.02854267 -0.2602364 -0.9214573 -2.610236 1
#> 3 1 -6.20 -2.30 0.98715561 1.1569931 -5.2128444 -1.143007 2
#> 4 1 -13.90 -2.55 0.03342283 1.0614358 -13.8665772 -1.488564 2
#> 5 1 -14.40 -5.80 -0.01490610 -0.1229999 -14.4149061 -5.923000 2
#> 6 1 -3.60 -1.70 3.19890631 0.3938729 -0.4010937 -1.306127 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -36900 7025
#> initial value 998.131940
#> iter 2 value 839.381554
#> iter 3 value 827.670726
#> iter 4 value 825.665146
#> iter 5 value 784.278678
#> iter 6 value 776.177329
#> iter 7 value 774.822840
#> iter 8 value 774.797450
#> iter 9 value 774.797412
#> iter 9 value 774.797401
#> iter 9 value 774.797396
#> final value 774.797396
#> converged
#> This is Run number 205
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6653152 0.2775223 -1.215315 -12.322478 1
#> 2 1 -0.95 -2.35 -0.3506892 0.9136511 -1.300689 -1.436349 1
#> 3 1 -6.20 -2.30 -0.3339382 4.8395650 -6.533938 2.539565 2
#> 4 1 -13.90 -2.55 0.6295637 1.0879722 -13.270436 -1.462028 2
#> 5 1 -14.40 -5.80 -0.4716169 -0.4118703 -14.871617 -6.211870 2
#> 6 1 -3.60 -1.70 0.1401795 -1.1066294 -3.459821 -2.806629 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -38450 6425
#> initial value 998.131940
#> iter 2 value 820.500551
#> iter 3 value 811.148662
#> iter 4 value 810.325943
#> iter 5 value 772.873807
#> iter 6 value 764.382310
#> iter 7 value 762.850214
#> iter 8 value 762.814215
#> iter 9 value 762.814132
#> iter 10 value 762.814118
#> iter 10 value 762.814109
#> iter 10 value 762.814105
#> final value 762.814105
#> converged
#> This is Run number 206
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.00562084 1.3004540 0.4556208 -11.299546 1
#> 2 1 -0.95 -2.35 1.35113052 0.5180916 0.4011305 -1.831908 1
#> 3 1 -6.20 -2.30 0.69321991 0.2222753 -5.5067801 -2.077725 2
#> 4 1 -13.90 -2.55 -0.53267292 -0.1220737 -14.4326729 -2.672074 2
#> 5 1 -14.40 -5.80 2.19095060 0.5133671 -12.2090494 -5.286633 2
#> 6 1 -3.60 -1.70 -0.01871406 0.5301702 -3.6187141 -1.169830 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6640 -38975 8000
#> initial value 998.131940
#> iter 2 value 803.832796
#> iter 3 value 789.484828
#> iter 4 value 789.203618
#> iter 5 value 753.507337
#> iter 6 value 744.940445
#> iter 7 value 743.754970
#> iter 8 value 743.734896
#> iter 9 value 743.734873
#> iter 9 value 743.734867
#> iter 9 value 743.734863
#> final value 743.734863
#> converged
#> This is Run number 207
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.79827061 -1.0301249 1.248271 -13.63012489 1
#> 2 1 -0.95 -2.35 -0.70996696 1.7787087 -1.659967 -0.57129125 2
#> 3 1 -6.20 -2.30 -0.69222404 0.1297352 -6.892224 -2.17026482 2
#> 4 1 -13.90 -2.55 1.28727624 2.4872409 -12.612724 -0.06275913 2
#> 5 1 -14.40 -5.80 -0.85938065 -0.8659836 -15.259381 -6.66598355 2
#> 6 1 -3.60 -1.70 0.09647942 -0.4644043 -3.503521 -2.16440430 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5460 -39225 7775
#> initial value 998.131940
#> iter 2 value 802.031969
#> iter 3 value 782.092187
#> iter 4 value 777.723227
#> iter 5 value 743.861703
#> iter 6 value 735.404082
#> iter 7 value 734.264279
#> iter 8 value 734.245285
#> iter 8 value 734.245277
#> final value 734.245277
#> converged
#> This is Run number 208
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.474340733 1.7911282 -0.07565927 -10.8088718 1
#> 2 1 -0.95 -2.35 -0.556423489 2.9628059 -1.50642349 0.6128059 2
#> 3 1 -6.20 -2.30 -1.296550267 0.3542291 -7.49655027 -1.9457709 2
#> 4 1 -13.90 -2.55 -0.832512501 0.1800411 -14.73251250 -2.3699589 2
#> 5 1 -14.40 -5.80 0.008062101 -0.1892226 -14.39193790 -5.9892226 2
#> 6 1 -3.60 -1.70 0.300677695 -0.3856469 -3.29932230 -2.0856469 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -38275 5350
#> initial value 998.131940
#> iter 2 value 827.439670
#> iter 3 value 821.366945
#> iter 4 value 820.756337
#> iter 5 value 782.650249
#> iter 6 value 774.309125
#> iter 7 value 772.441022
#> iter 8 value 772.393038
#> iter 9 value 772.392877
#> iter 10 value 772.392863
#> iter 10 value 772.392863
#> iter 10 value 772.392859
#> final value 772.392859
#> converged
#> This is Run number 209
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8225040 -0.1780247 0.272504 -12.7780247 1
#> 2 1 -0.95 -2.35 2.0999462 1.6790221 1.149946 -0.6709779 1
#> 3 1 -6.20 -2.30 1.2541799 3.1807898 -4.945820 0.8807898 2
#> 4 1 -13.90 -2.55 -1.1655911 0.1878590 -15.065591 -2.3621410 2
#> 5 1 -14.40 -5.80 -0.5826035 1.2253266 -14.982604 -4.5746734 2
#> 6 1 -3.60 -1.70 1.6363569 0.9918696 -1.963643 -0.7081304 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6080 -38725 7000
#> initial value 998.131940
#> iter 2 value 813.924157
#> iter 3 value 800.358844
#> iter 4 value 798.069634
#> iter 5 value 761.970917
#> iter 6 value 753.435851
#> iter 7 value 752.107717
#> iter 8 value 752.080088
#> iter 9 value 752.080048
#> iter 9 value 752.080038
#> iter 9 value 752.080032
#> final value 752.080032
#> converged
#> This is Run number 210
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0804471 1.6148739 -1.6304471 -10.9851261 1
#> 2 1 -0.95 -2.35 1.7314486 0.4688926 0.7814486 -1.8811074 1
#> 3 1 -6.20 -2.30 1.5239115 0.2387191 -4.6760885 -2.0612809 2
#> 4 1 -13.90 -2.55 -0.5629955 1.8695882 -14.4629955 -0.6804118 2
#> 5 1 -14.40 -5.80 -0.1106001 -0.1239423 -14.5106001 -5.9239423 2
#> 6 1 -3.60 -1.70 0.8496519 -0.3173498 -2.7503481 -2.0173498 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38525 5900
#> initial value 998.131940
#> iter 2 value 822.255128
#> iter 3 value 812.118377
#> iter 4 value 809.853369
#> iter 5 value 773.052328
#> iter 6 value 764.541898
#> iter 7 value 762.948070
#> iter 8 value 762.909123
#> iter 9 value 762.909023
#> iter 10 value 762.909011
#> iter 10 value 762.909011
#> iter 10 value 762.909006
#> final value 762.909006
#> converged
#> This is Run number 211
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.7381860 2.3702811 -1.288186 -10.229719 1
#> 2 1 -0.95 -2.35 -1.0710475 -0.3180330 -2.021048 -2.668033 1
#> 3 1 -6.20 -2.30 -0.1021724 0.1380649 -6.302172 -2.161935 2
#> 4 1 -13.90 -2.55 3.2012258 1.2632025 -10.698774 -1.286798 2
#> 5 1 -14.40 -5.80 0.3240949 -0.5851632 -14.075905 -6.385163 2
#> 6 1 -3.60 -1.70 -0.6865354 -1.2800631 -4.286535 -2.980063 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5640 -38125 7800
#> initial value 998.131940
#> iter 2 value 817.997227
#> iter 3 value 802.145859
#> iter 4 value 799.752160
#> iter 5 value 762.038148
#> iter 6 value 753.679818
#> iter 7 value 752.452537
#> iter 8 value 752.431655
#> iter 9 value 752.431635
#> iter 9 value 752.431629
#> iter 9 value 752.431629
#> final value 752.431629
#> converged
#> This is Run number 212
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5518995 0.7412249 -1.101900 -11.858775 1
#> 2 1 -0.95 -2.35 -1.2393277 -0.3694231 -2.189328 -2.719423 1
#> 3 1 -6.20 -2.30 2.7140459 0.6899771 -3.485954 -1.610023 2
#> 4 1 -13.90 -2.55 0.5622765 0.9551819 -13.337723 -1.594818 2
#> 5 1 -14.40 -5.80 -0.3327129 -0.1355594 -14.732713 -5.935559 2
#> 6 1 -3.60 -1.70 0.3038434 -1.2381983 -3.296157 -2.938198 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39400 5850
#> initial value 998.131940
#> iter 2 value 809.433833
#> iter 3 value 798.150084
#> iter 4 value 795.306960
#> iter 5 value 761.213008
#> iter 6 value 752.519260
#> iter 7 value 750.971687
#> iter 8 value 750.931472
#> iter 9 value 750.931362
#> iter 10 value 750.931350
#> iter 10 value 750.931349
#> iter 10 value 750.931343
#> final value 750.931343
#> converged
#> This is Run number 213
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8397235 0.8683139 0.2897235 -11.7316861 1
#> 2 1 -0.95 -2.35 -0.5890346 0.9158195 -1.5390346 -1.4341805 2
#> 3 1 -6.20 -2.30 2.0217331 0.8086952 -4.1782669 -1.4913048 2
#> 4 1 -13.90 -2.55 -1.1671817 0.2152469 -15.0671817 -2.3347531 2
#> 5 1 -14.40 -5.80 0.6411148 0.3520927 -13.7588852 -5.4479073 2
#> 6 1 -3.60 -1.70 0.1473700 1.2898364 -3.4526300 -0.4101636 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5560 -35925 6275
#> initial value 998.131940
#> iter 2 value 855.875285
#> iter 3 value 846.557284
#> iter 4 value 844.541095
#> iter 5 value 800.651093
#> iter 6 value 792.889076
#> iter 7 value 791.466039
#> iter 8 value 791.439678
#> iter 9 value 791.439632
#> iter 9 value 791.439631
#> iter 9 value 791.439631
#> final value 791.439631
#> converged
#> This is Run number 214
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5880903 1.72894066 0.03809032 -10.871059 1
#> 2 1 -0.95 -2.35 -1.3183744 0.02608701 -2.26837443 -2.323913 1
#> 3 1 -6.20 -2.30 -0.5867485 -0.76564477 -6.78674846 -3.065645 2
#> 4 1 -13.90 -2.55 2.5043098 0.68273099 -11.39569015 -1.867269 2
#> 5 1 -14.40 -5.80 3.0882450 -1.53274335 -11.31175496 -7.332743 2
#> 6 1 -3.60 -1.70 -1.2458252 -0.81017421 -4.84582520 -2.510174 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6380 -38750 7775
#> initial value 998.131940
#> iter 2 value 808.808801
#> iter 3 value 794.775476
#> iter 4 value 794.006426
#> iter 5 value 757.686181
#> iter 6 value 749.161460
#> iter 7 value 747.932226
#> iter 8 value 747.910021
#> iter 9 value 747.909995
#> iter 9 value 747.909988
#> iter 9 value 747.909986
#> final value 747.909986
#> converged
#> This is Run number 215
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.09169008 -0.1369218 -0.4583099 -12.7369218 1
#> 2 1 -0.95 -2.35 -0.09315536 -0.6526726 -1.0431554 -3.0026726 1
#> 3 1 -6.20 -2.30 -0.45936153 3.2561633 -6.6593615 0.9561633 2
#> 4 1 -13.90 -2.55 -0.26124703 -0.3651859 -14.1612470 -2.9151859 2
#> 5 1 -14.40 -5.80 1.02114270 1.0287486 -13.3788573 -4.7712514 2
#> 6 1 -3.60 -1.70 -0.30273714 0.8162572 -3.9027371 -0.8837428 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6000 -39350 7125
#> initial value 998.131940
#> iter 2 value 803.935733
#> iter 3 value 788.262130
#> iter 4 value 785.181803
#> iter 5 value 751.201637
#> iter 6 value 742.598680
#> iter 7 value 741.353379
#> iter 8 value 741.328242
#> iter 9 value 741.328214
#> iter 9 value 741.328206
#> iter 9 value 741.328201
#> final value 741.328201
#> converged
#> This is Run number 216
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2066983 2.6146710 -0.7566983 -9.9853290 1
#> 2 1 -0.95 -2.35 0.3564629 1.9682892 -0.5935371 -0.3817108 2
#> 3 1 -6.20 -2.30 1.0512524 1.6769366 -5.1487476 -0.6230634 2
#> 4 1 -13.90 -2.55 2.0165478 0.8636186 -11.8834522 -1.6863814 2
#> 5 1 -14.40 -5.80 1.2738111 0.2055095 -13.1261889 -5.5944905 2
#> 6 1 -3.60 -1.70 -0.4822271 -0.4540221 -4.0822271 -2.1540221 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5720 -37900 7275
#> initial value 998.131940
#> iter 2 value 824.311550
#> iter 3 value 810.335267
#> iter 4 value 807.912021
#> iter 5 value 769.479035
#> iter 6 value 761.124843
#> iter 7 value 759.819415
#> iter 8 value 759.794711
#> iter 9 value 759.794680
#> iter 9 value 759.794670
#> iter 9 value 759.794665
#> final value 759.794665
#> converged
#> This is Run number 217
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9269806 -0.4281532 0.3769806 -13.028153 1
#> 2 1 -0.95 -2.35 1.9402842 -0.3252042 0.9902842 -2.675204 1
#> 3 1 -6.20 -2.30 3.3392293 0.3297800 -2.8607707 -1.970220 2
#> 4 1 -13.90 -2.55 1.6926674 -0.6094662 -12.2073326 -3.159466 2
#> 5 1 -14.40 -5.80 3.9327639 -0.1386314 -10.4672361 -5.938631 2
#> 6 1 -3.60 -1.70 1.6349908 -1.3948699 -1.9650092 -3.094870 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -39075 7025
#> initial value 998.131940
#> iter 2 value 808.666363
#> iter 3 value 793.236179
#> iter 4 value 789.971672
#> iter 5 value 755.191358
#> iter 6 value 746.609712
#> iter 7 value 745.335143
#> iter 8 value 745.309189
#> iter 9 value 745.309157
#> iter 9 value 745.309150
#> iter 9 value 745.309145
#> final value 745.309145
#> converged
#> This is Run number 218
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.16000160 -0.03526239 -1.710002 -12.63526239 1
#> 2 1 -0.95 -2.35 -0.89423071 -0.64229143 -1.844231 -2.99229143 1
#> 3 1 -6.20 -2.30 -1.17382981 0.14981155 -7.373830 -2.15018845 2
#> 4 1 -13.90 -2.55 0.22575472 -0.32449013 -13.674245 -2.87449013 2
#> 5 1 -14.40 -5.80 -0.03684955 0.32234712 -14.436850 -5.47765288 2
#> 6 1 -3.60 -1.70 0.28921266 1.60723484 -3.310787 -0.09276516 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -38300 7725
#> initial value 998.131940
#> iter 2 value 815.900592
#> iter 3 value 801.140831
#> iter 4 value 799.430577
#> iter 5 value 762.025225
#> iter 6 value 753.610059
#> iter 7 value 752.369440
#> iter 8 value 752.347448
#> iter 9 value 752.347424
#> iter 9 value 752.347416
#> iter 9 value 752.347410
#> final value 752.347410
#> converged
#> This is Run number 219
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.91658657 3.91101543 -1.4665866 -8.688985 1
#> 2 1 -0.95 -2.35 0.08912086 0.07344246 -0.8608791 -2.276558 1
#> 3 1 -6.20 -2.30 1.74606889 0.59702546 -4.4539311 -1.702975 2
#> 4 1 -13.90 -2.55 2.04921261 0.42832508 -11.8507874 -2.121675 2
#> 5 1 -14.40 -5.80 1.52153305 -0.40264686 -12.8784670 -6.202647 2
#> 6 1 -3.60 -1.70 0.54033159 -0.86860529 -3.0596684 -2.568605 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6420 -38650 6850
#> initial value 998.131940
#> iter 2 value 815.638568
#> iter 3 value 804.051855
#> iter 4 value 802.712554
#> iter 5 value 766.072786
#> iter 6 value 757.535318
#> iter 7 value 756.138987
#> iter 8 value 756.108346
#> iter 9 value 756.108292
#> iter 10 value 756.108279
#> iter 10 value 756.108270
#> iter 10 value 756.108268
#> final value 756.108268
#> converged
#> This is Run number 220
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.0654828 0.6547639 -1.6154828 -11.94523608 1
#> 2 1 -0.95 -2.35 0.3993259 0.3562450 -0.5506741 -1.99375501 1
#> 3 1 -6.20 -2.30 2.7682318 1.1207055 -3.4317682 -1.17929447 2
#> 4 1 -13.90 -2.55 1.0575306 1.3948554 -12.8424694 -1.15514458 2
#> 5 1 -14.40 -5.80 2.4069026 0.2330548 -11.9930974 -5.56694521 2
#> 6 1 -3.60 -1.70 -1.1249150 1.7991393 -4.7249150 0.09913926 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5820 -37775 7350
#> initial value 998.131940
#> iter 2 value 825.601490
#> iter 3 value 812.297340
#> iter 4 value 810.377079
#> iter 5 value 771.446108
#> iter 6 value 763.119233
#> iter 7 value 761.810783
#> iter 8 value 761.786157
#> iter 9 value 761.786125
#> iter 9 value 761.786114
#> iter 9 value 761.786108
#> final value 761.786108
#> converged
#> This is Run number 221
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.9000783 -0.004409697 0.3500783 -12.604410 1
#> 2 1 -0.95 -2.35 -0.4800878 0.563000045 -1.4300878 -1.787000 1
#> 3 1 -6.20 -2.30 0.4041835 0.605752274 -5.7958165 -1.694248 2
#> 4 1 -13.90 -2.55 -0.7918820 0.761345481 -14.6918820 -1.788655 2
#> 5 1 -14.40 -5.80 0.8632203 0.200058745 -13.5367797 -5.599941 2
#> 6 1 -3.60 -1.70 0.8651042 0.042409954 -2.7348958 -1.657590 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -39000 7225
#> initial value 998.131940
#> iter 2 value 808.253020
#> iter 3 value 795.813338
#> iter 4 value 794.951389
#> iter 5 value 759.274754
#> iter 6 value 750.677054
#> iter 7 value 749.358660
#> iter 8 value 749.331012
#> iter 9 value 749.330969
#> iter 10 value 749.330956
#> iter 10 value 749.330946
#> iter 10 value 749.330939
#> final value 749.330939
#> converged
#> This is Run number 222
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5974888 0.7207872 -1.147489 -11.8792128 1
#> 2 1 -0.95 -2.35 2.4177932 1.2107015 1.467793 -1.1392985 1
#> 3 1 -6.20 -2.30 -0.9147225 0.8125029 -7.114723 -1.4874971 2
#> 4 1 -13.90 -2.55 0.9994110 2.1232375 -12.900589 -0.4267625 2
#> 5 1 -14.40 -5.80 -1.0913688 4.5534294 -15.491369 -1.2465706 2
#> 6 1 -3.60 -1.70 -0.0112052 -0.3993452 -3.611205 -2.0993452 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38075 7100
#> initial value 998.131940
#> iter 2 value 822.261078
#> iter 3 value 811.942835
#> iter 4 value 811.632289
#> iter 5 value 773.078012
#> iter 6 value 764.644017
#> iter 7 value 763.231041
#> iter 8 value 763.200911
#> iter 9 value 763.200851
#> iter 10 value 763.200835
#> iter 10 value 763.200825
#> iter 10 value 763.200818
#> final value 763.200818
#> converged
#> This is Run number 223
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.8476100 1.3207487 1.297610 -11.279251334 1
#> 2 1 -0.95 -2.35 -0.8531956 2.3562997 -1.803196 0.006299748 2
#> 3 1 -6.20 -2.30 1.3090482 -1.4392946 -4.890952 -3.739294611 2
#> 4 1 -13.90 -2.55 0.7109863 1.2417223 -13.189014 -1.308277719 2
#> 5 1 -14.40 -5.80 2.1710187 0.4505619 -12.228981 -5.349438056 2
#> 6 1 -3.60 -1.70 -1.3060764 -0.1635694 -4.906076 -1.863569387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6280 -37325 6150
#> initial value 998.131940
#> iter 2 value 837.964233
#> iter 3 value 829.286267
#> iter 4 value 827.941315
#> iter 5 value 787.517484
#> iter 6 value 779.333333
#> iter 7 value 777.774281
#> iter 8 value 777.740246
#> iter 9 value 777.740170
#> iter 9 value 777.740170
#> iter 9 value 777.740170
#> final value 777.740170
#> converged
#> This is Run number 224
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1452453 0.13098693 -1.6952453 -12.4690131 1
#> 2 1 -0.95 -2.35 0.3876162 0.77493437 -0.5623838 -1.5750656 1
#> 3 1 -6.20 -2.30 1.6711713 0.74241078 -4.5288287 -1.5575892 2
#> 4 1 -13.90 -2.55 -0.7816148 1.76706709 -14.6816148 -0.7829329 2
#> 5 1 -14.40 -5.80 0.4505547 -0.46879084 -13.9494453 -6.2687908 2
#> 6 1 -3.60 -1.70 0.3612035 0.07746109 -3.2387965 -1.6225389 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5960 -36850 6500
#> initial value 998.131940
#> iter 2 value 842.752952
#> iter 3 value 833.218933
#> iter 4 value 831.692715
#> iter 5 value 790.047163
#> iter 6 value 781.982992
#> iter 7 value 780.525025
#> iter 8 value 780.495636
#> iter 9 value 780.495581
#> iter 9 value 780.495578
#> iter 9 value 780.495578
#> final value 780.495578
#> converged
#> This is Run number 225
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.5534737 0.51978165 -1.103474 -12.080218 1
#> 2 1 -0.95 -2.35 2.2873416 0.72168668 1.337342 -1.628313 1
#> 3 1 -6.20 -2.30 2.7367478 0.46097836 -3.463252 -1.839022 2
#> 4 1 -13.90 -2.55 2.6558252 -0.38613520 -11.244175 -2.936135 2
#> 5 1 -14.40 -5.80 3.9567387 -0.21961638 -10.443261 -6.019616 2
#> 6 1 -3.60 -1.70 2.2565819 -0.01522072 -1.343418 -1.715221 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -38975 8025
#> initial value 998.131940
#> iter 2 value 804.001710
#> iter 3 value 788.334758
#> iter 4 value 787.279503
#> iter 5 value 751.775799
#> iter 6 value 743.269799
#> iter 7 value 742.099602
#> iter 8 value 742.080249
#> iter 9 value 742.080228
#> iter 9 value 742.080220
#> iter 9 value 742.080216
#> final value 742.080216
#> converged
#> This is Run number 226
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7441052 0.2947034 1.194105 -12.30529658 1
#> 2 1 -0.95 -2.35 -0.7036946 -1.5217352 -1.653695 -3.87173525 1
#> 3 1 -6.20 -2.30 0.6120319 1.3815294 -5.587968 -0.91847058 2
#> 4 1 -13.90 -2.55 0.9700783 2.5828218 -12.929922 0.03282182 2
#> 5 1 -14.40 -5.80 0.2687309 2.1144806 -14.131269 -3.68551941 2
#> 6 1 -3.60 -1.70 -1.2389821 0.4902838 -4.838982 -1.20971616 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7160 -38425 5725
#> initial value 998.131940
#> iter 2 value 823.668463
#> iter 3 value 816.850808
#> iter 4 value 816.408532
#> iter 5 value 778.669920
#> iter 6 value 770.251297
#> iter 7 value 768.484599
#> iter 8 value 768.439764
#> iter 9 value 768.439627
#> iter 10 value 768.439613
#> iter 10 value 768.439609
#> iter 10 value 768.439606
#> final value 768.439606
#> converged
#> This is Run number 227
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.4441583 2.6284613 2.894158 -9.9715387 1
#> 2 1 -0.95 -2.35 -1.0597370 0.4807928 -2.009737 -1.8692072 2
#> 3 1 -6.20 -2.30 0.2773811 2.1961445 -5.922619 -0.1038555 2
#> 4 1 -13.90 -2.55 -0.8482658 1.0370210 -14.748266 -1.5129790 2
#> 5 1 -14.40 -5.80 0.1758028 -0.3642346 -14.224197 -6.1642346 2
#> 6 1 -3.60 -1.70 1.4461426 0.4603274 -2.153857 -1.2396726 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6220 -36625 5775
#> initial value 998.131940
#> iter 2 value 849.049071
#> iter 3 value 841.696413
#> iter 4 value 840.394412
#> iter 5 value 798.144243
#> iter 6 value 790.213110
#> iter 7 value 788.605465
#> iter 8 value 788.571698
#> iter 9 value 788.571618
#> iter 9 value 788.571608
#> iter 9 value 788.571604
#> final value 788.571604
#> converged
#> This is Run number 228
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.0447475 -0.40380582 -0.5052525 -13.0038058 1
#> 2 1 -0.95 -2.35 3.5619603 1.67717616 2.6119603 -0.6728238 1
#> 3 1 -6.20 -2.30 0.7238402 3.03673666 -5.4761598 0.7367367 2
#> 4 1 -13.90 -2.55 0.7806459 -0.08152807 -13.1193541 -2.6315281 2
#> 5 1 -14.40 -5.80 0.9494378 1.00268280 -13.4505622 -4.7973172 2
#> 6 1 -3.60 -1.70 -0.5529688 0.98569664 -4.1529688 -0.7143034 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5500 -36900 7075
#> initial value 998.131940
#> iter 2 value 839.113520
#> iter 3 value 826.637404
#> iter 4 value 824.257472
#> iter 5 value 782.968090
#> iter 6 value 774.862478
#> iter 7 value 773.525022
#> iter 8 value 773.500427
#> iter 9 value 773.500393
#> iter 9 value 773.500383
#> iter 9 value 773.500378
#> final value 773.500378
#> converged
#> This is Run number 229
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.9852670 2.5355131 1.4352670 -10.0644869 1
#> 2 1 -0.95 -2.35 1.1320253 1.9968171 0.1820253 -0.3531829 1
#> 3 1 -6.20 -2.30 -0.6673611 -1.0597203 -6.8673611 -3.3597203 2
#> 4 1 -13.90 -2.55 1.0495013 1.3418826 -12.8504987 -1.2081174 2
#> 5 1 -14.40 -5.80 -0.8831389 0.1121219 -15.2831389 -5.6878781 2
#> 6 1 -3.60 -1.70 1.0609421 2.1497227 -2.5390579 0.4497227 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -37525 7850
#> initial value 998.131940
#> iter 2 value 825.892580
#> iter 3 value 813.272609
#> iter 4 value 812.660445
#> iter 5 value 772.686939
#> iter 6 value 764.388726
#> iter 7 value 763.125869
#> iter 8 value 763.104057
#> iter 9 value 763.104028
#> iter 9 value 763.104020
#> iter 9 value 763.104012
#> final value 763.104012
#> converged
#> This is Run number 230
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.03255199 2.7785120 -0.517448 -9.8214880 1
#> 2 1 -0.95 -2.35 2.77938134 1.2514665 1.829381 -1.0985335 1
#> 3 1 -6.20 -2.30 -0.21063749 -0.5963459 -6.410637 -2.8963459 2
#> 4 1 -13.90 -2.55 1.91723859 3.5261275 -11.982761 0.9761275 2
#> 5 1 -14.40 -5.80 0.72171373 0.8986288 -13.678286 -4.9013712 2
#> 6 1 -3.60 -1.70 0.61462267 0.4009530 -2.985377 -1.2990470 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -38025 8150
#> initial value 998.131940
#> iter 2 value 817.132946
#> iter 3 value 801.813499
#> iter 4 value 800.504616
#> iter 5 value 762.214966
#> iter 6 value 753.869159
#> iter 7 value 752.672882
#> iter 8 value 752.654045
#> iter 9 value 752.654027
#> iter 9 value 752.654020
#> iter 9 value 752.654016
#> final value 752.654016
#> converged
#> This is Run number 231
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.73531656 -1.530465749 -1.285317 -14.1304657 1
#> 2 1 -0.95 -2.35 -0.48852775 2.150363214 -1.438528 -0.1996368 2
#> 3 1 -6.20 -2.30 0.10929049 -0.962438246 -6.090710 -3.2624382 2
#> 4 1 -13.90 -2.55 0.11701363 -1.239015260 -13.782986 -3.7890153 2
#> 5 1 -14.40 -5.80 -0.35429037 0.002149594 -14.754290 -5.7978504 2
#> 6 1 -3.60 -1.70 -0.05224961 2.132736925 -3.652250 0.4327369 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -39450 7575
#> initial value 998.131940
#> iter 2 value 799.503982
#> iter 3 value 784.965112
#> iter 4 value 783.844908
#> iter 5 value 749.690918
#> iter 6 value 741.080205
#> iter 7 value 739.869311
#> iter 8 value 739.846278
#> iter 9 value 739.846252
#> iter 9 value 739.846244
#> iter 9 value 739.846243
#> final value 739.846243
#> converged
#> This is Run number 232
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8773840 -0.03556040 -1.4273840 -12.6355604 1
#> 2 1 -0.95 -2.35 1.5218759 3.73471566 0.5718759 1.3847157 2
#> 3 1 -6.20 -2.30 -0.7278281 -0.01909818 -6.9278281 -2.3190982 2
#> 4 1 -13.90 -2.55 1.0088512 0.66409343 -12.8911488 -1.8859066 2
#> 5 1 -14.40 -5.80 3.3750571 0.66021795 -11.0249429 -5.1397820 2
#> 6 1 -3.60 -1.70 0.3978376 1.34839978 -3.2021624 -0.3516002 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38800 6175
#> initial value 998.131940
#> iter 2 value 817.016408
#> iter 3 value 805.408360
#> iter 4 value 802.782092
#> iter 5 value 766.891990
#> iter 6 value 758.309422
#> iter 7 value 756.814807
#> iter 8 value 756.779226
#> iter 9 value 756.779148
#> iter 9 value 756.779137
#> iter 9 value 756.779131
#> final value 756.779131
#> converged
#> This is Run number 233
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.48119914 0.7116074 -1.031199 -11.8883926 1
#> 2 1 -0.95 -2.35 -0.44626121 0.1265621 -1.396261 -2.2234379 1
#> 3 1 -6.20 -2.30 0.08820424 0.6102511 -6.111796 -1.6897489 2
#> 4 1 -13.90 -2.55 0.58974194 -1.2617690 -13.310258 -3.8117690 2
#> 5 1 -14.40 -5.80 -0.15078747 4.0017594 -14.550787 -1.7982406 2
#> 6 1 -3.60 -1.70 2.03602961 1.5876173 -1.563970 -0.1123827 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6360 -39025 6975
#> initial value 998.131940
#> iter 2 value 809.472073
#> iter 3 value 796.658382
#> iter 4 value 794.968249
#> iter 5 value 759.567558
#> iter 6 value 750.973226
#> iter 7 value 749.635459
#> iter 8 value 749.606661
#> iter 9 value 749.606616
#> iter 10 value 749.606605
#> iter 10 value 749.606597
#> iter 10 value 749.606591
#> final value 749.606591
#> converged
#> This is Run number 234
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.20312965 -0.4369401 -0.7531296 -13.036940 1
#> 2 1 -0.95 -2.35 1.58038645 -0.5655113 0.6303864 -2.915511 1
#> 3 1 -6.20 -2.30 0.68258610 -0.3409222 -5.5174139 -2.640922 2
#> 4 1 -13.90 -2.55 1.08750589 -0.4550891 -12.8124941 -3.005089 2
#> 5 1 -14.40 -5.80 -0.09852209 -1.1345732 -14.4985221 -6.934573 2
#> 6 1 -3.60 -1.70 -0.64938331 -1.0224924 -4.2493833 -2.722492 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6620 -40700 6375
#> initial value 998.131940
#> iter 2 value 786.396879
#> iter 3 value 772.502015
#> iter 4 value 769.353571
#> iter 5 value 739.332176
#> iter 6 value 730.547941
#> iter 7 value 729.276095
#> iter 8 value 729.245000
#> iter 9 value 729.244945
#> iter 9 value 729.244939
#> iter 9 value 729.244933
#> final value 729.244933
#> converged
#> This is Run number 235
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.80982266 1.4263786 -1.3598227 -11.173621 1
#> 2 1 -0.95 -2.35 1.27694536 0.9225383 0.3269454 -1.427462 1
#> 3 1 -6.20 -2.30 2.98622402 -0.3988181 -3.2137760 -2.698818 2
#> 4 1 -13.90 -2.55 -0.36101653 0.3252803 -14.2610165 -2.224720 2
#> 5 1 -14.40 -5.80 -0.07688913 0.3382052 -14.4768891 -5.461795 2
#> 6 1 -3.60 -1.70 -0.33120811 0.2577318 -3.9312081 -1.442268 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5980 -38925 7200
#> initial value 998.131940
#> iter 2 value 809.888783
#> iter 3 value 794.990142
#> iter 4 value 792.372727
#> iter 5 value 757.001830
#> iter 6 value 748.455523
#> iter 7 value 747.182970
#> iter 8 value 747.157635
#> iter 9 value 747.157605
#> iter 9 value 747.157596
#> iter 9 value 747.157591
#> final value 747.157591
#> converged
#> This is Run number 236
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7965914 -0.04870332 1.246591 -12.6487033 1
#> 2 1 -0.95 -2.35 -0.3530705 -0.35677258 -1.303071 -2.7067726 1
#> 3 1 -6.20 -2.30 0.6195920 -0.69061997 -5.580408 -2.9906200 2
#> 4 1 -13.90 -2.55 0.6252621 1.19040595 -13.274738 -1.3595940 2
#> 5 1 -14.40 -5.80 0.5936413 -0.27481174 -13.806359 -6.0748117 2
#> 6 1 -3.60 -1.70 -0.5563107 2.55929414 -4.156311 0.8592941 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5900 -38250 7375
#> initial value 998.131940
#> iter 2 value 818.729364
#> iter 3 value 804.677775
#> iter 4 value 802.616641
#> iter 5 value 765.113626
#> iter 6 value 756.689200
#> iter 7 value 755.400449
#> iter 8 value 755.375906
#> iter 9 value 755.375875
#> iter 9 value 755.375865
#> iter 9 value 755.375859
#> final value 755.375859
#> converged
#> This is Run number 237
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.00448599 0.5773295 -1.554486 -12.02267052 1
#> 2 1 -0.95 -2.35 -1.05295748 2.4025245 -2.002957 0.05252447 2
#> 3 1 -6.20 -2.30 -0.17379317 4.6904100 -6.373793 2.39041002 2
#> 4 1 -13.90 -2.55 0.08746244 -0.7566977 -13.812538 -3.30669772 2
#> 5 1 -14.40 -5.80 0.30851843 1.6665333 -14.091482 -4.13346667 2
#> 6 1 -3.60 -1.70 0.53126972 0.2393648 -3.068730 -1.46063515 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6240 -39125 7100
#> initial value 998.131940
#> iter 2 value 807.356921
#> iter 3 value 793.531199
#> iter 4 value 791.502450
#> iter 5 value 756.531381
#> iter 6 value 747.937458
#> iter 7 value 746.641842
#> iter 8 value 746.614866
#> iter 9 value 746.614830
#> iter 9 value 746.614820
#> iter 9 value 746.614814
#> final value 746.614814
#> converged
#> This is Run number 238
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.8405225 1.2268711 0.2905225 -11.3731289 1
#> 2 1 -0.95 -2.35 -0.1030576 0.2193215 -1.0530576 -2.1306785 1
#> 3 1 -6.20 -2.30 0.6144532 1.3732119 -5.5855468 -0.9267881 2
#> 4 1 -13.90 -2.55 -0.2888606 -0.9605566 -14.1888606 -3.5105566 2
#> 5 1 -14.40 -5.80 0.2597323 2.3425253 -14.1402677 -3.4574747 2
#> 6 1 -3.60 -1.70 -0.6243951 0.1923333 -4.2243951 -1.5076667 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6260 -38050 6900
#> initial value 998.131940
#> iter 2 value 824.087932
#> iter 3 value 812.903341
#> iter 4 value 811.618463
#> iter 5 value 773.234850
#> iter 6 value 764.827717
#> iter 7 value 763.423150
#> iter 8 value 763.393480
#> iter 9 value 763.393428
#> iter 10 value 763.393414
#> iter 10 value 763.393404
#> iter 10 value 763.393400
#> final value 763.393400
#> converged
#> This is Run number 239
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.1772484 0.2126690 2.6272484 -12.387331 1
#> 2 1 -0.95 -2.35 0.0816046 0.2679445 -0.8683954 -2.082055 1
#> 3 1 -6.20 -2.30 -0.2190574 0.3126964 -6.4190574 -1.987304 2
#> 4 1 -13.90 -2.55 0.9748933 1.1207130 -12.9251067 -1.429287 2
#> 5 1 -14.40 -5.80 2.5001654 0.1922016 -11.8998346 -5.607798 2
#> 6 1 -3.60 -1.70 0.2016867 -0.2987466 -3.3983133 -1.998747 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6560 -39400 6925
#> initial value 998.131940
#> iter 2 value 803.957698
#> iter 3 value 791.377019
#> iter 4 value 789.925105
#> iter 5 value 755.555420
#> iter 6 value 746.898259
#> iter 7 value 745.564684
#> iter 8 value 745.535133
#> iter 9 value 745.535085
#> iter 10 value 745.535074
#> iter 10 value 745.535065
#> iter 10 value 745.535060
#> final value 745.535060
#> converged
#> This is Run number 240
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 5.0093042 1.02414952 4.459304 -11.57585048 1
#> 2 1 -0.95 -2.35 3.3717477 0.58398147 2.421748 -1.76601853 1
#> 3 1 -6.20 -2.30 -0.5433670 2.35125957 -6.743367 0.05125957 2
#> 4 1 -13.90 -2.55 0.4631510 0.70165006 -13.436849 -1.84834994 2
#> 5 1 -14.40 -5.80 0.4880912 0.03061548 -13.911909 -5.76938452 2
#> 6 1 -3.60 -1.70 1.9404469 0.27519715 -1.659553 -1.42480285 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -38775 7350
#> initial value 998.131940
#> iter 2 value 810.726593
#> iter 3 value 798.730358
#> iter 4 value 798.302582
#> iter 5 value 761.871486
#> iter 6 value 753.298017
#> iter 7 value 751.974126
#> iter 8 value 751.946825
#> iter 9 value 751.946781
#> iter 10 value 751.946766
#> iter 10 value 751.946757
#> iter 10 value 751.946749
#> final value 751.946749
#> converged
#> This is Run number 241
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.31016368 0.8647829 -0.8601637 -11.7352171 1
#> 2 1 -0.95 -2.35 1.11268413 3.9797480 0.1626841 1.6297480 2
#> 3 1 -6.20 -2.30 0.35103620 0.9718929 -5.8489638 -1.3281071 2
#> 4 1 -13.90 -2.55 -0.52632554 -0.3870442 -14.4263255 -2.9370442 2
#> 5 1 -14.40 -5.80 -0.01124584 -0.2165955 -14.4112458 -6.0165955 2
#> 6 1 -3.60 -1.70 -0.87348806 1.3790042 -4.4734881 -0.3209958 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6720 -40375 6750
#> initial value 998.131940
#> iter 2 value 789.591202
#> iter 3 value 776.204988
#> iter 4 value 774.224881
#> iter 5 value 742.933012
#> iter 6 value 734.183495
#> iter 7 value 732.917333
#> iter 8 value 732.888181
#> iter 9 value 732.888137
#> iter 9 value 732.888137
#> iter 9 value 732.888137
#> final value 732.888137
#> converged
#> This is Run number 242
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6494390 1.54342819 0.09943900 -11.0565718 1
#> 2 1 -0.95 -2.35 1.0192253 0.08960209 0.06922532 -2.2603979 1
#> 3 1 -6.20 -2.30 -0.3140770 2.96674827 -6.51407703 0.6667483 2
#> 4 1 -13.90 -2.55 -0.3208263 2.28910240 -14.22082633 -0.2608976 2
#> 5 1 -14.40 -5.80 1.5841395 -0.17950177 -12.81586051 -5.9795018 2
#> 6 1 -3.60 -1.70 0.5659185 -0.62849461 -3.03408154 -2.3284946 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -37400 6400
#> initial value 998.131940
#> iter 2 value 835.178170
#> iter 3 value 827.635495
#> iter 4 value 827.446241
#> iter 5 value 786.873888
#> iter 6 value 778.675208
#> iter 7 value 777.085423
#> iter 8 value 777.049741
#> iter 9 value 777.049650
#> iter 10 value 777.049634
#> iter 10 value 777.049625
#> iter 10 value 777.049616
#> final value 777.049616
#> converged
#> This is Run number 243
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.4805062 3.0838861 1.93050618 -9.516114 1
#> 2 1 -0.95 -2.35 1.0495383 -0.1520628 0.09953833 -2.502063 1
#> 3 1 -6.20 -2.30 1.9789513 -0.7203178 -4.22104871 -3.020318 2
#> 4 1 -13.90 -2.55 0.8635060 0.1326368 -13.03649397 -2.417363 2
#> 5 1 -14.40 -5.80 0.2057064 2.3673315 -14.19429357 -3.432668 2
#> 6 1 -3.60 -1.70 0.3295832 -0.4042369 -3.27041683 -2.104237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38850 6225
#> initial value 998.131940
#> iter 2 value 815.947555
#> iter 3 value 804.900656
#> iter 4 value 802.724024
#> iter 5 value 766.852562
#> iter 6 value 758.269569
#> iter 7 value 756.768084
#> iter 8 value 756.732173
#> iter 9 value 756.732095
#> iter 9 value 756.732084
#> iter 9 value 756.732078
#> final value 756.732078
#> converged
#> This is Run number 244
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.655043227 1.22161720 0.1050432 -11.3783828 1
#> 2 1 -0.95 -2.35 -0.002454318 -0.24362416 -0.9524543 -2.5936242 1
#> 3 1 -6.20 -2.30 -1.006912432 -0.09113768 -7.2069124 -2.3911377 2
#> 4 1 -13.90 -2.55 -0.549814037 3.38010125 -14.4498140 0.8301013 2
#> 5 1 -14.40 -5.80 1.731383699 1.19105735 -12.6686163 -4.6089427 2
#> 6 1 -3.60 -1.70 -0.477807517 1.59538957 -4.0778075 -0.1046104 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6120 -38175 7600
#> initial value 998.131940
#> iter 2 value 818.360246
#> iter 3 value 804.983630
#> iter 4 value 803.822680
#> iter 5 value 765.866144
#> iter 6 value 757.446109
#> iter 7 value 756.170251
#> iter 8 value 756.146611
#> iter 9 value 756.146580
#> iter 9 value 756.146569
#> iter 9 value 756.146563
#> final value 756.146563
#> converged
#> This is Run number 245
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.8445037 0.4627549 2.294504 -12.1372451 1
#> 2 1 -0.95 -2.35 -0.1232785 0.0791009 -1.073279 -2.2708991 1
#> 3 1 -6.20 -2.30 0.5272793 -1.0085839 -5.672721 -3.3085839 2
#> 4 1 -13.90 -2.55 1.9527666 -0.9632221 -11.947233 -3.5132221 2
#> 5 1 -14.40 -5.80 0.9935716 2.0774481 -13.406428 -3.7225519 2
#> 6 1 -3.60 -1.70 1.8113113 1.1359141 -1.788689 -0.5640859 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5860 -36750 6000
#> initial value 998.131940
#> iter 2 value 846.554042
#> iter 3 value 837.205108
#> iter 4 value 835.097604
#> iter 5 value 793.376229
#> iter 6 value 785.348486
#> iter 7 value 783.819987
#> iter 8 value 783.788448
#> iter 9 value 783.788381
#> iter 9 value 783.788372
#> iter 9 value 783.788368
#> final value 783.788368
#> converged
#> This is Run number 246
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.1947171 1.2179700 1.6447171 -11.3820300 1
#> 2 1 -0.95 -2.35 1.2186088 1.7841259 0.2686088 -0.5658741 1
#> 3 1 -6.20 -2.30 1.4122247 0.9045920 -4.7877753 -1.3954080 2
#> 4 1 -13.90 -2.55 0.1791404 -0.5492948 -13.7208596 -3.0992948 2
#> 5 1 -14.40 -5.80 1.6302392 1.9455393 -12.7697608 -3.8544607 2
#> 6 1 -3.60 -1.70 -0.9766555 0.2611104 -4.5766555 -1.4388896 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -38300 6525
#> initial value 998.131940
#> iter 2 value 822.181386
#> iter 3 value 812.747373
#> iter 4 value 811.998231
#> iter 5 value 774.108233
#> iter 6 value 765.647492
#> iter 7 value 764.133339
#> iter 8 value 764.098441
#> iter 9 value 764.098363
#> iter 10 value 764.098348
#> iter 10 value 764.098338
#> iter 10 value 764.098333
#> final value 764.098333
#> converged
#> This is Run number 247
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2088165 0.5931075 0.6588165 -12.006892 1
#> 2 1 -0.95 -2.35 0.4808139 -1.0211328 -0.4691861 -3.371133 1
#> 3 1 -6.20 -2.30 3.5088141 0.4158355 -2.6911859 -1.884164 2
#> 4 1 -13.90 -2.55 0.8408609 -0.0235867 -13.0591391 -2.573587 2
#> 5 1 -14.40 -5.80 -0.5046380 -0.7710901 -14.9046380 -6.571090 2
#> 6 1 -3.60 -1.70 2.1141948 -0.7719867 -1.4858052 -2.471987 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -38200 6125
#> initial value 998.131940
#> iter 2 value 825.987177
#> iter 3 value 815.241085
#> iter 4 value 812.885430
#> iter 5 value 775.191752
#> iter 6 value 766.746118
#> iter 7 value 765.214787
#> iter 8 value 765.179433
#> iter 9 value 765.179354
#> iter 9 value 765.179343
#> iter 9 value 765.179338
#> final value 765.179338
#> converged
#> This is Run number 248
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.02810859 -0.61540022 -0.5218914 -13.2154002 1
#> 2 1 -0.95 -2.35 -1.27613975 0.54502206 -2.2261397 -1.8049779 2
#> 3 1 -6.20 -2.30 0.14504544 0.40146568 -6.0549546 -1.8985343 2
#> 4 1 -13.90 -2.55 2.08761878 0.05451075 -11.8123812 -2.4954893 2
#> 5 1 -14.40 -5.80 1.33323333 0.58618945 -13.0667667 -5.2138106 2
#> 6 1 -3.60 -1.70 0.42835266 2.52480226 -3.1716473 0.8248023 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6680 -40875 6800
#> initial value 998.131940
#> iter 2 value 781.280346
#> iter 3 value 766.563653
#> iter 4 value 763.997399
#> iter 5 value 734.433159
#> iter 6 value 725.700456
#> iter 7 value 724.523136
#> iter 8 value 724.496845
#> iter 9 value 724.496813
#> iter 9 value 724.496812
#> iter 9 value 724.496812
#> final value 724.496812
#> converged
#> This is Run number 249
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.6333742 -0.7362471 -2.1833742 -13.3362471 1
#> 2 1 -0.95 -2.35 -0.7205674 0.5910431 -1.6705674 -1.7589569 1
#> 3 1 -6.20 -2.30 0.4194497 3.6669410 -5.7805503 1.3669410 2
#> 4 1 -13.90 -2.55 0.8342635 2.3644905 -13.0657365 -0.1855095 2
#> 5 1 -14.40 -5.80 -0.4914265 0.7035326 -14.8914265 -5.0964674 2
#> 6 1 -3.60 -1.70 4.4156025 1.8720871 0.8156025 0.1720871 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6200 -36725 6500
#> initial value 998.131940
#> iter 2 value 844.266208
#> iter 3 value 835.862053
#> iter 4 value 834.980809
#> iter 5 value 792.810447
#> iter 6 value 784.796024
#> iter 7 value 783.312871
#> iter 8 value 783.282686
#> iter 9 value 783.282623
#> iter 9 value 783.282619
#> iter 9 value 783.282619
#> final value 783.282619
#> converged
#> This is Run number 250
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.7381788 1.5872388 1.188179 -11.0127612 1
#> 2 1 -0.95 -2.35 -0.7568609 2.6698661 -1.706861 0.3198661 2
#> 3 1 -6.20 -2.30 2.1164821 0.8411596 -4.083518 -1.4588404 2
#> 4 1 -13.90 -2.55 0.3853132 1.0538036 -13.514687 -1.4961964 2
#> 5 1 -14.40 -5.80 0.5614486 -0.2464262 -13.838551 -6.0464262 2
#> 6 1 -3.60 -1.70 -0.2661704 0.8739728 -3.866170 -0.8260272 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5760 -36625 6350
#> initial value 998.131940
#> iter 2 value 846.527470
#> iter 3 value 836.680841
#> iter 4 value 834.681412
#> iter 5 value 792.580035
#> iter 6 value 784.580769
#> iter 7 value 783.124309
#> iter 8 value 783.095515
#> iter 9 value 783.095462
#> iter 9 value 783.095461
#> iter 9 value 783.095461
#> final value 783.095461
#> converged
#> This is Run number 251
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.1561369 0.7081376 -1.7061369 -11.8918624 1
#> 2 1 -0.95 -2.35 1.4298268 5.7933276 0.4798268 3.4433276 2
#> 3 1 -6.20 -2.30 2.3851884 -0.8059106 -3.8148116 -3.1059106 2
#> 4 1 -13.90 -2.55 -0.8106951 1.2064598 -14.7106951 -1.3435402 2
#> 5 1 -14.40 -5.80 -0.8619319 1.3703933 -15.2619319 -4.4296067 2
#> 6 1 -3.60 -1.70 0.4952075 2.3965973 -3.1047925 0.6965973 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38150 6675
#> initial value 998.131940
#> iter 2 value 823.951017
#> iter 3 value 812.417941
#> iter 4 value 810.512955
#> iter 5 value 772.582669
#> iter 6 value 764.152880
#> iter 7 value 762.728128
#> iter 8 value 762.697398
#> iter 9 value 762.697342
#> iter 9 value 762.697342
#> iter 9 value 762.697342
#> final value 762.697342
#> converged
#> This is Run number 252
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 2.5596742 0.55386934 2.009674 -12.0461307 1
#> 2 1 -0.95 -2.35 -0.2015699 2.93604776 -1.151570 0.5860478 2
#> 3 1 -6.20 -2.30 -0.1707201 -0.07179202 -6.370720 -2.3717920 2
#> 4 1 -13.90 -2.55 -0.1397897 0.04092373 -14.039790 -2.5090763 2
#> 5 1 -14.40 -5.80 -0.3211993 2.73792648 -14.721199 -3.0620735 2
#> 6 1 -3.60 -1.70 0.3891829 1.58555717 -3.210817 -0.1144428 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6180 -39125 6675
#> initial value 998.131940
#> iter 2 value 809.707936
#> iter 3 value 796.307177
#> iter 4 value 793.614386
#> iter 5 value 758.761945
#> iter 6 value 750.140558
#> iter 7 value 748.781748
#> iter 8 value 748.751536
#> iter 9 value 748.751486
#> iter 9 value 748.751477
#> iter 9 value 748.751472
#> final value 748.751472
#> converged
#> This is Run number 253
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.6197171 0.999364053 -1.169717 -11.600636 1
#> 2 1 -0.95 -2.35 1.1803660 0.557361371 0.230366 -1.792639 1
#> 3 1 -6.20 -2.30 2.7702375 -0.938393045 -3.429762 -3.238393 2
#> 4 1 -13.90 -2.55 -1.0333665 0.000621511 -14.933366 -2.549378 2
#> 5 1 -14.40 -5.80 5.6772584 0.337473267 -8.722742 -5.462527 2
#> 6 1 -3.60 -1.70 0.7180809 -1.523482153 -2.881919 -3.223482 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6700 -40025 7325
#> initial value 998.131940
#> iter 2 value 791.919262
#> iter 3 value 777.766786
#> iter 4 value 776.609688
#> iter 5 value 744.145843
#> iter 6 value 735.460709
#> iter 7 value 734.252548
#> iter 8 value 734.227952
#> iter 9 value 734.227923
#> iter 9 value 734.227913
#> iter 9 value 734.227906
#> final value 734.227906
#> converged
#> This is Run number 254
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 4.1904158 2.59241227 3.6404158 -10.0075877 1
#> 2 1 -0.95 -2.35 0.6318071 2.14138571 -0.3181929 -0.2086143 2
#> 3 1 -6.20 -2.30 -0.4486886 0.32046953 -6.6486886 -1.9795305 2
#> 4 1 -13.90 -2.55 3.4114280 0.03430246 -10.4885720 -2.5156975 2
#> 5 1 -14.40 -5.80 -0.7089325 2.62019631 -15.1089325 -3.1798037 2
#> 6 1 -3.60 -1.70 6.6011162 -0.72163302 3.0011162 -2.4216330 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -38750 7500
#> initial value 998.131940
#> iter 2 value 810.634163
#> iter 3 value 796.418401
#> iter 4 value 794.857008
#> iter 5 value 758.707181
#> iter 6 value 750.192886
#> iter 7 value 748.934718
#> iter 8 value 748.910741
#> iter 9 value 748.910713
#> iter 9 value 748.910703
#> iter 9 value 748.910696
#> final value 748.910696
#> converged
#> This is Run number 255
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.4402523 -0.9887353 -0.1097477 -13.5887353 1
#> 2 1 -0.95 -2.35 1.5494531 2.8822533 0.5994531 0.5322533 1
#> 3 1 -6.20 -2.30 0.7975385 -0.4613180 -5.4024615 -2.7613180 2
#> 4 1 -13.90 -2.55 0.8567760 -0.9043923 -13.0432240 -3.4543923 2
#> 5 1 -14.40 -5.80 0.2642116 -0.6270664 -14.1357884 -6.4270664 2
#> 6 1 -3.60 -1.70 0.4927658 1.8388325 -3.1072342 0.1388325 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6660 -39125 6500
#> initial value 998.131940
#> iter 2 value 810.270795
#> iter 3 value 799.443926
#> iter 4 value 798.081893
#> iter 5 value 762.782520
#> iter 6 value 754.152172
#> iter 7 value 752.695273
#> iter 8 value 752.660657
#> iter 9 value 752.660586
#> iter 10 value 752.660574
#> iter 10 value 752.660567
#> iter 10 value 752.660561
#> final value 752.660561
#> converged
#> This is Run number 256
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2436453 1.18896074 -0.7936453 -11.411039 1
#> 2 1 -0.95 -2.35 2.2454091 -0.11922326 1.2954091 -2.469223 1
#> 3 1 -6.20 -2.30 -0.2637810 0.42521340 -6.4637810 -1.874787 2
#> 4 1 -13.90 -2.55 -0.5819784 2.42218098 -14.4819784 -0.127819 2
#> 5 1 -14.40 -5.80 4.0508737 -0.01946365 -10.3491263 -5.819464 2
#> 6 1 -3.60 -1.70 1.3757228 2.77810478 -2.2242772 1.078105 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6100 -40625 8150
#> initial value 998.131940
#> iter 2 value 777.662101
#> iter 3 value 757.006316
#> iter 4 value 754.138877
#> iter 5 value 724.325319
#> iter 6 value 715.943653
#> iter 7 value 714.935922
#> iter 8 value 714.920615
#> iter 9 value 714.920604
#> iter 9 value 714.920598
#> iter 9 value 714.920598
#> final value 714.920598
#> converged
#> This is Run number 257
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.27071338 -0.3540568 0.7207134 -12.9540568 1
#> 2 1 -0.95 -2.35 0.07494138 0.4708555 -0.8750586 -1.8791445 1
#> 3 1 -6.20 -2.30 1.49787382 1.5970045 -4.7021262 -0.7029955 2
#> 4 1 -13.90 -2.55 0.04792892 -0.3201371 -13.8520711 -2.8701371 2
#> 5 1 -14.40 -5.80 0.50897854 0.7292844 -13.8910215 -5.0707156 2
#> 6 1 -3.60 -1.70 0.36966777 -0.3580409 -3.2303322 -2.0580409 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7040 -39325 6300
#> initial value 998.131940
#> iter 2 value 807.854068
#> iter 3 value 798.454167
#> iter 4 value 797.719068
#> iter 5 value 762.759881
#> iter 6 value 754.095581
#> iter 7 value 752.556624
#> iter 8 value 752.517842
#> iter 9 value 752.517749
#> iter 10 value 752.517734
#> iter 10 value 752.517727
#> iter 10 value 752.517720
#> final value 752.517720
#> converged
#> This is Run number 258
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.33196803 2.0588522 -0.2180320 -10.541148 1
#> 2 1 -0.95 -2.35 0.12840013 -0.2039175 -0.8215999 -2.553917 1
#> 3 1 -6.20 -2.30 -0.08936058 0.1248208 -6.2893606 -2.175179 2
#> 4 1 -13.90 -2.55 0.89975357 0.4167752 -13.0002464 -2.133225 2
#> 5 1 -14.40 -5.80 -0.44046379 -0.2346377 -14.8404638 -6.034638 2
#> 6 1 -3.60 -1.70 0.52815807 0.3637958 -3.0718419 -1.336204 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6040 -38150 6875
#> initial value 998.131940
#> iter 2 value 822.927788
#> iter 3 value 810.617600
#> iter 4 value 808.600803
#> iter 5 value 770.726039
#> iter 6 value 762.298998
#> iter 7 value 760.918630
#> iter 8 value 760.889857
#> iter 9 value 760.889811
#> iter 9 value 760.889800
#> iter 9 value 760.889794
#> final value 760.889794
#> converged
#> This is Run number 259
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.8780564 2.20764333 -1.428056 -10.392357 1
#> 2 1 -0.95 -2.35 1.4397950 -1.50001471 0.489795 -3.850015 1
#> 3 1 -6.20 -2.30 -0.2169486 -0.91174839 -6.416949 -3.211748 2
#> 4 1 -13.90 -2.55 -0.1822472 -0.09998267 -14.082247 -2.649983 2
#> 5 1 -14.40 -5.80 0.6001515 -0.08210979 -13.799849 -5.882110 2
#> 6 1 -3.60 -1.70 1.7128590 -1.49172820 -1.887141 -3.191728 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6480 -40025 7825
#> initial value 998.131940
#> iter 2 value 789.078234
#> iter 3 value 772.664622
#> iter 4 value 771.347166
#> iter 5 value 739.089936
#> iter 6 value 730.502929
#> iter 7 value 729.385127
#> iter 8 value 729.365821
#> iter 9 value 729.365800
#> iter 9 value 729.365792
#> iter 9 value 729.365786
#> final value 729.365786
#> converged
#> This is Run number 260
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.2026689 -0.2758724 0.6526689 -12.8758724 1
#> 2 1 -0.95 -2.35 -1.5887154 3.0894023 -2.5387154 0.7394023 2
#> 3 1 -6.20 -2.30 1.0129490 -0.3665425 -5.1870510 -2.6665425 2
#> 4 1 -13.90 -2.55 2.8700788 0.7383350 -11.0299212 -1.8116650 2
#> 5 1 -14.40 -5.80 3.1028744 -0.5085462 -11.2971256 -6.3085462 2
#> 6 1 -3.60 -1.70 0.0027649 0.4068498 -3.5972351 -1.2931502 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5680 -37750 7200
#> initial value 998.131940
#> iter 2 value 826.843666
#> iter 3 value 813.126525
#> iter 4 value 810.641819
#> iter 5 value 771.784682
#> iter 6 value 763.460592
#> iter 7 value 762.142673
#> iter 8 value 762.117632
#> iter 9 value 762.117600
#> iter 9 value 762.117590
#> iter 9 value 762.117585
#> final value 762.117585
#> converged
#> This is Run number 261
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.03938052 1.1927672 -0.5893805 -11.4072328 1
#> 2 1 -0.95 -2.35 3.13432496 0.2028294 2.1843250 -2.1471706 1
#> 3 1 -6.20 -2.30 -0.42791980 0.1915672 -6.6279198 -2.1084328 2
#> 4 1 -13.90 -2.55 2.85895386 -0.5962267 -11.0410461 -3.1462267 2
#> 5 1 -14.40 -5.80 -0.93648301 -1.1104720 -15.3364830 -6.9104720 2
#> 6 1 -3.60 -1.70 0.08913710 1.0899383 -3.5108629 -0.6100617 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5360 -37550 7425
#> initial value 998.131940
#> iter 2 value 828.307070
#> iter 3 value 812.975935
#> iter 4 value 809.816103
#> iter 5 value 770.574733
#> iter 6 value 762.307716
#> iter 7 value 761.032284
#> iter 8 value 761.009774
#> iter 9 value 761.009751
#> iter 9 value 761.009742
#> iter 9 value 761.009738
#> final value 761.009738
#> converged
#> This is Run number 262
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.1425067 -1.4406223 -0.4074933 -14.04062235 1
#> 2 1 -0.95 -2.35 0.1678418 1.3499121 -0.7821582 -1.00008795 1
#> 3 1 -6.20 -2.30 -0.1230280 -0.6759555 -6.3230280 -2.97595551 2
#> 4 1 -13.90 -2.55 2.4721228 2.4826997 -11.4278772 -0.06730028 2
#> 5 1 -14.40 -5.80 0.5183590 -0.4281362 -13.8816410 -6.22813621 2
#> 6 1 -3.60 -1.70 -0.4999486 1.1265143 -4.0999486 -0.57348566 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38925 7800
#> initial value 998.131940
#> iter 2 value 806.010915
#> iter 3 value 791.830837
#> iter 4 value 791.153079
#> iter 5 value 755.342687
#> iter 6 value 746.791024
#> iter 7 value 745.574160
#> iter 8 value 745.552279
#> iter 8 value 745.552272
#> final value 745.552272
#> converged
#> This is Run number 263
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6377269 -0.50416279 0.08772691 -13.104163 1
#> 2 1 -0.95 -2.35 -0.5738979 -0.01040989 -1.52389790 -2.360410 1
#> 3 1 -6.20 -2.30 1.0005281 -0.16308516 -5.19947187 -2.463085 2
#> 4 1 -13.90 -2.55 0.7276166 0.29187939 -13.17238336 -2.258121 2
#> 5 1 -14.40 -5.80 2.3134102 3.51299710 -12.08658979 -2.287003 2
#> 6 1 -3.60 -1.70 1.7366259 -0.12815988 -1.86337412 -1.828160 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 5920 -37100 6550
#> initial value 998.131940
#> iter 2 value 839.187781
#> iter 3 value 828.928431
#> iter 4 value 827.146195
#> iter 5 value 786.245981
#> iter 6 value 778.098462
#> iter 7 value 776.651350
#> iter 8 value 776.621914
#> iter 9 value 776.621860
#> iter 9 value 776.621858
#> iter 9 value 776.621858
#> final value 776.621858
#> converged
#> This is Run number 264
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.6209664 0.6631102 0.07096643 -11.9368898 1
#> 2 1 -0.95 -2.35 0.8757897 -1.5785130 -0.07421032 -3.9285130 1
#> 3 1 -6.20 -2.30 -0.5101587 3.4580951 -6.71015870 1.1580951 2
#> 4 1 -13.90 -2.55 -0.2240903 0.8752780 -14.12409029 -1.6747220 2
#> 5 1 -14.40 -5.80 0.9276813 3.3713160 -13.47231873 -2.4286840 2
#> 6 1 -3.60 -1.70 -0.1044358 1.1091605 -3.70443581 -0.5908395 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6020 -37825 7100
#> initial value 998.131940
#> iter 2 value 826.266903
#> iter 3 value 814.185859
#> iter 4 value 812.588821
#> iter 5 value 773.680367
#> iter 6 value 765.331249
#> iter 7 value 763.973071
#> iter 8 value 763.945951
#> iter 9 value 763.945909
#> iter 10 value 763.945897
#> iter 10 value 763.945887
#> iter 10 value 763.945885
#> final value 763.945885
#> converged
#> This is Run number 265
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.2552601 -0.08744323 -0.8052601 -12.687443 1
#> 2 1 -0.95 -2.35 -0.8589044 1.28768019 -1.8089044 -1.062320 2
#> 3 1 -6.20 -2.30 0.9168319 0.22914383 -5.2831681 -2.070856 2
#> 4 1 -13.90 -2.55 0.5863428 0.47770852 -13.3136572 -2.072291 2
#> 5 1 -14.40 -5.80 -1.8810551 -0.27699357 -16.2810551 -6.076994 2
#> 6 1 -3.60 -1.70 2.2326590 -0.95832001 -1.3673410 -2.658320 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38000 7000
#> initial value 998.131940
#> iter 2 value 824.199771
#> iter 3 value 813.149956
#> iter 4 value 812.129540
#> iter 5 value 773.535088
#> iter 6 value 765.136071
#> iter 7 value 763.739798
#> iter 8 value 763.710586
#> iter 9 value 763.710534
#> iter 10 value 763.710520
#> iter 10 value 763.710509
#> iter 10 value 763.710507
#> final value 763.710507
#> converged
#> This is Run number 266
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.5521719 2.1162354 0.002171926 -10.483765 1
#> 2 1 -0.95 -2.35 0.9513936 -0.7059960 0.001393558 -3.055996 1
#> 3 1 -6.20 -2.30 1.0143771 1.0757955 -5.185622869 -1.224204 2
#> 4 1 -13.90 -2.55 1.4865684 -0.3557861 -12.413431599 -2.905786 2
#> 5 1 -14.40 -5.80 0.3326057 0.8715644 -14.067394292 -4.928436 2
#> 6 1 -3.60 -1.70 -0.5109481 0.1392917 -4.110948112 -1.560708 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6160 -37575 7950
#> initial value 998.131940
#> iter 2 value 824.547919
#> iter 3 value 811.706234
#> iter 4 value 811.198739
#> iter 5 value 771.355225
#> iter 6 value 763.040429
#> iter 7 value 761.793135
#> iter 8 value 761.772096
#> iter 8 value 761.772095
#> final value 761.772095
#> converged
#> This is Run number 267
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 3.6418425 1.1239771 3.09184245 -11.4760229 1
#> 2 1 -0.95 -2.35 0.9290501 -0.5259110 -0.02094991 -2.8759110 1
#> 3 1 -6.20 -2.30 1.8655929 1.3855948 -4.33440705 -0.9144052 2
#> 4 1 -13.90 -2.55 0.6335735 4.4043032 -13.26642652 1.8543032 2
#> 5 1 -14.40 -5.80 1.3032937 0.4693574 -13.09670632 -5.3306426 2
#> 6 1 -3.60 -1.70 -1.5845678 3.6242659 -5.18456785 1.9242659 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 7080 -38775 6875
#> initial value 998.131940
#> iter 2 value 812.963624
#> iter 3 value 803.078116
#> iter 4 value 802.940144
#> iter 5 value 766.323858
#> iter 6 value 757.748867
#> iter 7 value 756.287536
#> iter 8 value 756.253636
#> iter 9 value 756.253561
#> iter 10 value 756.253542
#> iter 10 value 756.253533
#> iter 10 value 756.253525
#> final value 756.253525
#> converged
#> This is Run number 268
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.85863948 -0.4506675 1.3086395 -13.050668 1
#> 2 1 -0.95 -2.35 0.04596431 -1.5868603 -0.9040357 -3.936860 1
#> 3 1 -6.20 -2.30 -1.23894270 0.2192232 -7.4389427 -2.080777 2
#> 4 1 -13.90 -2.55 -1.77185545 -0.4983418 -15.6718554 -3.048342 2
#> 5 1 -14.40 -5.80 -0.40853453 0.2119774 -14.8085345 -5.588023 2
#> 6 1 -3.60 -1.70 0.50957777 -0.4919903 -3.0904222 -2.191990 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6840 -39725 5950
#> initial value 998.131940
#> iter 2 value 803.676913
#> iter 3 value 793.477023
#> iter 4 value 791.586709
#> iter 5 value 758.173955
#> iter 6 value 749.450544
#> iter 7 value 747.901674
#> iter 8 value 747.860808
#> iter 9 value 747.860704
#> iter 10 value 747.860691
#> iter 10 value 747.860691
#> iter 10 value 747.860685
#> final value 747.860685
#> converged
#> This is Run number 269
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.7718741 -0.3199869 0.2218741 -12.9199869 1
#> 2 1 -0.95 -2.35 -0.3593836 -0.6087115 -1.3093836 -2.9587115 1
#> 3 1 -6.20 -2.30 -0.2082694 0.4688898 -6.4082694 -1.8311102 2
#> 4 1 -13.90 -2.55 1.1035857 0.4758437 -12.7964143 -2.0741563 2
#> 5 1 -14.40 -5.80 1.2532171 2.1069011 -13.1467829 -3.6930989 2
#> 6 1 -3.60 -1.70 0.1925566 1.2763763 -3.4074434 -0.4236237 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6400 -38225 6325
#> initial value 998.131940
#> iter 2 value 824.513406
#> iter 3 value 814.505051
#> iter 4 value 812.957506
#> iter 5 value 775.096424
#> iter 6 value 766.656763
#> iter 7 value 765.137024
#> iter 8 value 765.102162
#> iter 9 value 765.102086
#> iter 10 value 765.102074
#> iter 10 value 765.102068
#> iter 10 value 765.102064
#> final value 765.102064
#> converged
#> This is Run number 270
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.60425824 0.3128764 1.0542582 -12.287124 1
#> 2 1 -0.95 -2.35 0.07235627 3.5707550 -0.8776437 1.220755 2
#> 3 1 -6.20 -2.30 0.96356455 -0.1455178 -5.2364354 -2.445518 2
#> 4 1 -13.90 -2.55 1.17866977 0.7324385 -12.7213302 -1.817561 2
#> 5 1 -14.40 -5.80 0.68413629 0.6136341 -13.7158637 -5.186366 2
#> 6 1 -3.60 -1.70 -0.25629799 -0.1790901 -3.8562980 -1.879090 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6320 -38800 6125
#> initial value 998.131940
#> iter 2 value 817.221522
#> iter 3 value 805.990434
#> iter 4 value 803.505758
#> iter 5 value 767.572377
#> iter 6 value 758.993323
#> iter 7 value 757.478627
#> iter 8 value 757.442193
#> iter 9 value 757.442111
#> iter 9 value 757.442100
#> iter 9 value 757.442094
#> final value 757.442094
#> converged
#> This is Run number 271
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 1.3979533 -0.3033646 0.8479533 -12.9033646 1
#> 2 1 -0.95 -2.35 1.2403548 -0.1480009 0.2903548 -2.4980009 1
#> 3 1 -6.20 -2.30 0.0979576 -0.4825124 -6.1020424 -2.7825124 2
#> 4 1 -13.90 -2.55 -0.5131946 2.7826686 -14.4131946 0.2326686 2
#> 5 1 -14.40 -5.80 1.4826828 0.8766343 -12.9173172 -4.9233657 2
#> 6 1 -3.60 -1.70 0.7357638 1.2998386 -2.8642362 -0.4001614 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6140 -38450 7975
#> initial value 998.131940
#> iter 2 value 812.070245
#> iter 3 value 797.297561
#> iter 4 value 796.294107
#> iter 5 value 759.173788
#> iter 6 value 750.725941
#> iter 7 value 749.518966
#> iter 8 value 749.498661
#> iter 9 value 749.498644
#> iter 9 value 749.498641
#> iter 10 value 749.498626
#> iter 10 value 749.498616
#> iter 10 value 749.498614
#> final value 749.498614
#> converged
#> This is Run number 272
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.2048856 0.7941502 -0.3451144 -11.8058498 1
#> 2 1 -0.95 -2.35 1.4538246 1.3645683 0.5038246 -0.9854317 1
#> 3 1 -6.20 -2.30 1.7738528 0.3578582 -4.4261472 -1.9421418 2
#> 4 1 -13.90 -2.55 1.4193496 2.0273056 -12.4806504 -0.5226944 2
#> 5 1 -14.40 -5.80 -0.4247481 3.9689190 -14.8247481 -1.8310810 2
#> 6 1 -3.60 -1.70 4.8461607 -0.4444106 1.2461607 -2.1444106 1
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -38625 7300
#> initial value 998.131940
#> iter 2 value 813.436569
#> iter 3 value 801.091505
#> iter 4 value 800.236617
#> iter 5 value 763.462989
#> iter 6 value 754.932131
#> iter 7 value 753.609375
#> iter 8 value 753.582383
#> iter 9 value 753.582341
#> iter 10 value 753.582327
#> iter 10 value 753.582318
#> iter 10 value 753.582311
#> final value 753.582311
#> converged
#> This is Run number 273
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -1.2631006 -0.4689069 -1.813101 -13.068907 1
#> 2 1 -0.95 -2.35 -1.1052696 0.4636591 -2.055270 -1.886341 2
#> 3 1 -6.20 -2.30 -0.4097308 -0.2536360 -6.609731 -2.553636 2
#> 4 1 -13.90 -2.55 -0.7447861 4.4598698 -14.644786 1.909870 2
#> 5 1 -14.40 -5.80 2.4652082 -0.6402120 -11.934792 -6.440212 2
#> 6 1 -3.60 -1.70 -0.9450787 -0.2502349 -4.545079 -1.950235 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6580 -36225 6400
#> initial value 998.131940
#> iter 2 value 850.892455
#> iter 3 value 844.306361
#> iter 4 value 844.158057
#> iter 5 value 800.508369
#> iter 6 value 792.693377
#> iter 7 value 791.161015
#> iter 8 value 791.129950
#> iter 9 value 791.129874
#> iter 9 value 791.129871
#> iter 9 value 791.129871
#> final value 791.129871
#> converged
#> This is Run number 274
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 -0.77612950 -0.3865490 -1.3261295 -12.9865490 1
#> 2 1 -0.95 -2.35 0.05689359 0.3934569 -0.8931064 -1.9565431 1
#> 3 1 -6.20 -2.30 0.70066342 -0.8065447 -5.4993366 -3.1065447 2
#> 4 1 -13.90 -2.55 -0.86424704 -1.6095553 -14.7642470 -4.1595553 2
#> 5 1 -14.40 -5.80 1.63653758 1.2759479 -12.7634624 -4.5240521 2
#> 6 1 -3.60 -1.70 1.39532466 2.5278723 -2.2046753 0.8278723 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6460 -39600 7900
#> initial value 998.131940
#> iter 2 value 795.211057
#> iter 3 value 779.397964
#> iter 4 value 778.392022
#> iter 5 value 744.756702
#> iter 6 value 736.178833
#> iter 7 value 735.032101
#> iter 8 value 735.012473
#> iter 9 value 735.012451
#> iter 9 value 735.012444
#> iter 9 value 735.012435
#> final value 735.012435
#> converged
#> This is Run number 275
#> does sou_gis exist: FALSE
#>
#> dataset final_set exists: FALSE
#>
#> decisiongroups exists: TRUE
#> 1 2
#> 1007 433
#>
#> data has been created
#>
#> First few observations of the dataset
#> ID Choice_situation alt1_x1 alt1_x2 alt1_x3 alt2_x1 alt2_x2 alt2_x3 Block
#> 1 1 7 80 25 100 60 200 100 1
#> 2 1 19 20 25 50 60 25 0 1
#> 3 1 30 20 100 50 80 50 100 1
#> 4 1 32 40 200 25 80 25 0 1
#> 5 1 39 40 200 0 80 100 100 1
#> 6 1 48 60 50 25 20 50 100 1
#> group V_1 V_2 e_1 e_2 U_1 U_2 CHOICE
#> 1 1 -0.55 -12.60 0.16437206 2.3694129 -0.3856279 -10.230587 1
#> 2 1 -0.95 -2.35 0.07988825 -0.3717487 -0.8701117 -2.721749 1
#> 3 1 -6.20 -2.30 0.26699233 -0.4774439 -5.9330077 -2.777444 2
#> 4 1 -13.90 -2.55 1.86501522 -0.3565152 -12.0349848 -2.906515 2
#> 5 1 -14.40 -5.80 -1.77503947 -0.3541150 -16.1750395 -6.154115 2
#> 6 1 -3.60 -1.70 -1.63781093 -0.5333874 -5.2378109 -2.233387 2
#>
#>
#> Initial function value: -998.1319
#> Initial gradient value:
#> bpreis blade bwarte
#> 6940 -40675 8075
#> initial value 998.131940
#> iter 2 value 776.661939
#> iter 3 value 759.798327
#> iter 4 value 759.358912
#> iter 5 value 728.963762
#> iter 6 value 720.395247
#> iter 7 value 719.362215
#> iter 8 value 719.346455
#> iter 9 value 719.34