From d65d5483364f69b0a7460ce7bdc251efafc6b4d1 Mon Sep 17 00:00:00 2001 From: hanneoberman Date: Thu, 17 Mar 2022 13:31:04 +0100 Subject: [PATCH] Update readme after CRAN acceptance --- CRAN-SUBMISSION | 4 ++-- README.Rmd | 14 ++++++++++---- README.md | 26 ++++++++++++++++++-------- 3 files changed, 30 insertions(+), 14 deletions(-) diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION index 6a0f9bfe..a75d09f4 100644 --- a/CRAN-SUBMISSION +++ b/CRAN-SUBMISSION @@ -1,3 +1,3 @@ Version: 0.0.1 -Date: 2022-03-15 16:49:59 UTC -SHA: dcfcfa5a0bc6f945790ed2b5d3051eba7ff08161 +Date: 2022-03-16 18:36:30 UTC +SHA: f3e7e2fcbf1516bda983f82159b30806c739d48f diff --git a/README.Rmd b/README.Rmd index c579d11f..910830d6 100644 --- a/README.Rmd +++ b/README.Rmd @@ -24,13 +24,19 @@ set.seed(1) [![Codecov test coverage](https://codecov.io/gh/amices/ggmice/branch/main/graph/badge.svg)](https://app.codecov.io/gh/amices/ggmice?branch=main) -## Plotting package for incomplete and imputed data +## Visualizations for `mice` with `ggplot2` -The `ggmice` package enhances imputation package `mice` with `ggplot2` visualizations. See the [vignette](https://amices.org/ggmice/articles/ggmice.html) for an overview of `ggmice`'s functionalities. +Enhance a `mice` imputation workflow with visualizations for incomplete and/or imputed data. The plotting functions produce `ggplot` objects which may be easily manipulated or extended. Use `ggmice` to inspect missing data, develop imputation models, evaluate algorithmic convergence, or compare observed versus imputed data. ## Installation -You can install the development version of `ggmice` from [GitHub](https://github.com/amices) with: +You can install the latest `ggmice` release from [CRAN](https://cran.r-project.org/) with: + +``` r +install.packages("ggmice") +``` + +Alternatively, you could install the development version of `ggmice` from [GitHub](https://github.com/amices) with: ``` r # install.packages("devtools") @@ -39,7 +45,7 @@ devtools::install_github("amices/ggmice") ## Example -Visualize missing data in an incomplete dataset, or evaluate imputed data against the observed data. +Visualize missing data in an incomplete dataset, or evaluate imputed data against the observed data.See the [`ggmice` vignette](https://amices.org/ggmice/articles/ggmice.html) for an overview of all functionalities. ```{r example} # load the package and some data diff --git a/README.md b/README.md index 8153983a..2a815a08 100644 --- a/README.md +++ b/README.md @@ -15,17 +15,25 @@ experimental](https://img.shields.io/badge/lifecycle-experimental-orange.svg)](h coverage](https://codecov.io/gh/amices/ggmice/branch/main/graph/badge.svg)](https://app.codecov.io/gh/amices/ggmice?branch=main) -## Plotting package for incomplete and imputed data +## Visualizations for `mice` with `ggplot2` -The `ggmice` package enhances imputation package `mice` with `ggplot2` -visualizations. See the -[vignette](https://amices.org/ggmice/articles/ggmice.html) for an -overview of `ggmice`’s functionalities. +Enhance a `mice` imputation workflow with visualizations for incomplete +and/or imputed data. The plotting functions produce `ggplot` objects +which may be easily manipulated or extended. Use `ggmice` to inspect +missing data, develop imputation models, evaluate algorithmic +convergence, or compare observed versus imputed data. ## Installation -You can install the development version of `ggmice` from -[GitHub](https://github.com/amices) with: +You can install the latest `ggmice` release from +[CRAN](https://cran.r-project.org/) with: + +``` r +install.packages("ggmice") +``` + +Alternatively, you could install the development version of `ggmice` +from [GitHub](https://github.com/amices) with: ``` r # install.packages("devtools") @@ -35,7 +43,9 @@ devtools::install_github("amices/ggmice") ## Example Visualize missing data in an incomplete dataset, or evaluate imputed -data against the observed data. +data against the observed data.See the [`ggmice` +vignette](https://amices.org/ggmice/articles/ggmice.html) for an +overview of all functionalities. ``` r # load the package and some data