From d9a2f48fc582682b01632a5718c739e1a26b98be Mon Sep 17 00:00:00 2001
From: Andrew Pulsipher <a.pulsipher@utah.edu>
Date: Mon, 4 Nov 2024 13:20:12 -0700
Subject: [PATCH] Fill out fields for roxygen docs of LFMCMC

---
 R/LFMCMC.R    | 69 ++++++++++++++++++++++++++++++++++++++++++++-----
 man/LFMCMC.Rd | 71 +++++++++++++++++++++++++++++++++++++++++++++------
 2 files changed, 126 insertions(+), 14 deletions(-)

diff --git a/R/LFMCMC.R b/R/LFMCMC.R
index 20a64e5c..efcc8a8c 100644
--- a/R/LFMCMC.R
+++ b/R/LFMCMC.R
@@ -3,14 +3,71 @@
 #'
 #' @aliases epiworld_lfmcmc
 #' @details
-#' TODO: Detail LFMCMC
+#' Performs a Likelihood-Free Markhov Chain Monte Carlo simulation
 #' @param model A model of class [epiworld_model]
 #' @returns
-#' - The `LFMCMC`function returns a model of class [epiworld_lfmcmc].
+#' The `LFMCMC` function returns a model of class [epiworld_lfmcmc].
 #' @examples
-#' model_sir <- ModelSIR(name = "COVID-19", prevalence = 0.01,
-#'   transmission_rate = 0.9, recovery_rate = 0.1)
-#' model_lfmcmc <- LFMCMC(model_sir)
+#' ## Setup an SIR model to use in the simulation
+#' model_seed <- 122
+#' model_sir <- ModelSIR(name = "COVID-19", prevalence = .1,
+#'   transmission_rate = .9, recovery_rate = .3)
+#' agents_smallworld(
+#'   model_sir,
+#'   n = 1000,
+#'   k = 5,
+#'   d = FALSE,
+#'   p = 0.01
+#' )
+#' verbose_off(model_sir)
+#' run(model_sir, ndays = 50, seed = model_seed)
+#'
+#' ## Setup LFMCMC
+#' # Extract the observed data from the model
+#' obs_data <- unname(as.integer(get_today_total(model_sir)))
+#'
+#' # Define the simulation function
+#' simfun <- function(params) {
+#'   set_param(model_sir, "Recovery rate", params[1])
+#'   set_param(model_sir, "Transmission rate", params[2])
+#'   run(model_sir, ndays = 50)
+#'   res <- unname(as.integer(get_today_total(model_sir)))
+#'   return(res)
+#' }
+#'
+#' # Define the summary function
+#' sumfun <- function(dat) {
+#'   return(dat)
+#' }
+#'
+#' # Create the LFMCMC model
+#' lfmcmc_model <- LFMCMC(model_sir) |>
+#'   set_simulation_fun(simfun) |>
+#'   set_summary_fun(sumfun) |>
+#'   use_proposal_norm_reflective() |>
+#'   use_kernel_fun_gaussian() |>
+#'   set_observed_data(obs_data)
+#'
+#' ## Run LFMCMC simulation
+#' # Set initial parameters
+#' par0 <- as.double(c(0.1, 0.5))
+#' n_samp <- 2000
+#' epsil <- as.double(1.0)
+#'
+#' # Run the LFMCMC simulation
+#' run_lfmcmc(
+#'   lfmcmc = lfmcmc_model,
+#'   params_init_ = par0,
+#'   n_samples_ = n_samp,
+#'   epsilon_ = epsil,
+#'   seed = model_seed
+#' )
+#'
+#' # Print the results
+#' set_stats_names(lfmcmc_model, get_states(model_sir))
+#' set_par_names(lfmcmc_model, c("Immune recovery", "Infectiousness"))
+#'
+#' print(lfmcmc_model)
 #' @export
 LFMCMC <- function(model) {
   if (!inherits(model, "epiworld_model"))
@@ -28,7 +85,7 @@ LFMCMC <- function(model) {
 #' @param n_samples_ Number of samples
 #' @param epsilon_ Epsilon parameter
 #' @param seed Random engine seed
-#' @returns The simulated model of class `epiworld_lfmcmc`.
+#' @returns The simulated model of class [epiworld_lfmcmc].
 #' @export
 run_lfmcmc <- function(lfmcmc, params_init_, n_samples_, epsilon_, seed = NULL) UseMethod("run_lfmcmc")
 
diff --git a/man/LFMCMC.Rd b/man/LFMCMC.Rd
index eaa6d427..3081b364 100644
--- a/man/LFMCMC.Rd
+++ b/man/LFMCMC.Rd
@@ -64,11 +64,9 @@ set_stats_names(lfmcmc, names)
 \item{...}{Ignored}
 }
 \value{
-\itemize{
-\item The \code{LFMCMC}function returns a model of class \link{epiworld_lfmcmc}.
-}
+The \code{LFMCMC} function returns a model of class \link{epiworld_lfmcmc}.
 
-The simulated model of class \code{epiworld_lfmcmc}.
+The simulated model of class \link{epiworld_lfmcmc}.
 
 The lfmcmc model with the observed data added
 
@@ -94,10 +92,67 @@ The lfmcmc model
 Likelihood-Free Markhov Chain Monte Carlo (LFMCMC)
 }
 \details{
-TODO: Detail LFMCMC
+Performs a Likelihood-Free Markhov Chain Monte Carlo simulation
 }
 \examples{
-model_sir <- ModelSIR(name = "COVID-19", prevalence = 0.01,
-  transmission_rate = 0.9, recovery_rate = 0.1)
-model_lfmcmc <- LFMCMC(model_sir)
+## Setup an SIR model to use in the simulation
+model_seed <- 122
+model_sir <- ModelSIR(name = "COVID-19", prevalence = .1, 
+ transmission_rate = .9, recovery_rate = .3)
+agents_smallworld(
+  model_sir,
+  n = 1000,
+  k = 5,
+  d = FALSE,
+  p = 0.01
+)
+verbose_off(model_sir)
+run(model_sir, ndays = 50, seed = model_seed)
+
+## Setup LFMCMC
+# Extract the observed data from the model
+obs_data <- unname(as.integer(get_today_total(model_sir)))
+
+# Define the simulation function
+simfun <- function(params) {
+  set_param(model_sir, "Recovery rate", params[1])
+  set_param(model_sir, "Transmission rate", params[2])
+  run(model_sir, ndays = 50)
+  res <- unname(as.integer(get_today_total(model_sir)))
+  return(res)
+}
+
+# Define the summary function
+sumfun <- function(dat) {
+  return(dat)
+}
+
+# Create the LFMCMC model
+lfmcmc_model <- LFMCMC(model_sir) |>
+  set_simulation_fun(simfun) |>
+  set_summary_fun(sumfun) |>
+  use_proposal_norm_reflective() |>
+  use_kernel_fun_gaussian() |>
+  set_observed_data(obs_data)
+
+## Run LFMCMC simulation
+# Set initial parameters
+par0 <- as.double(c(0.1, 0.5))
+n_samp <- 2000
+epsil <- as.double(1.0)
+
+# Run the LFMCMC simulation
+run_lfmcmc(
+  lfmcmc = lfmcmc_model,
+  params_init_ = par0,
+  n_samples_ = n_samp,
+  epsilon_ = epsil,
+  seed = model_seed
+)
+
+# Print the results
+set_stats_names(lfmcmc_model, get_states(model_sir))
+set_par_names(lfmcmc_model, c("Immune recovery", "Infectiousness"))
+
+print(lfmcmc_model)
 }