add beta.proposal in MH sampler

Author: zhizuio

NEWS.md

@@ -1,10 +1,11 @@
 <div style="text-align: left;">
 
-### GPTCM 1.1.4 (2025-10-31)
+### GPTCM 1.1.4 (2025-11-21)
 
 * Update survival curve's ylab in vignette
+* Add option for using coefficients' proposals in the MH's proposal ratio
 
-### GPTCM 1.1.3 (2025-10-31)
+### GPTCM 1.1.3 (2025-11-01)
 
 * Remove redundant variables `logPosteriorZeta` and `logPosteriorBeta` in cpp files
 * Remove partial likelihood `loglikelihood0()`, and always use joint likelihood

R/GPTCM.R

@@ -27,6 +27,8 @@
 #' parametrization of the Dirichlet regression model
 #' @param hyperpar a list of relevant hyperparameters
 #' @param BVS logical value for implementing Bayesian variable selection
+#' @param beta.proposal logical value to determine if betas' proposal is used in MH's proposal ratio for gammas
+#' @param zeta.proposal logical value to determine if zetas' proposal is used in MH's proposal ratio for etas
 #' @param threads maximum threads used for parallelization. Default is 1
 #' @param kappaIGamma logical value for using inverse-gamma prior (\code{TRUE})
 #' or gamma prior (\code{FALSE}) for Weibull's shape parameter
@@ -90,6 +92,8 @@ GPTCM <- function(dat,
                   dirichlet = TRUE,
                   hyperpar = NULL,
                   BVS = TRUE,
+                  beta.proposal = FALSE,
+                  zeta.proposal = FALSE,
                   threads = 1,
                   kappaIGamma = FALSE,
                   kappaSampler = "arms",
@@ -317,6 +321,8 @@ GPTCM <- function(dat,
     dirichlet,
     proportion.model,
     BVS,
+    beta.proposal,
+    zeta.proposal,
     threads,
     gammaPrior,
     gammaSampler,

R/RcppExports.R

@@ -16,6 +16,8 @@
 #' @param dirichlet not yet implemented
 #' @param proportion_model logical value for modeling the proportions data
 #' @param BVS logical value for implementing Bayesian variable selection
+#' @param beta_proposal logical value to determine if betas' proposal is used in MH's proposal ratio for gammas
+#' @param zeta_proposal logical value to determine if zetas' proposal is used in MH's proposal ratio for etas
 #' @param threads maximum threads used for parallelization. Default is 1
 #' @param gamma_prior one of \code{c("bernoulli", "MRF")}
 #' @param gamma_sampler one of \code{c("mc3", "bandit")}
@@ -30,7 +32,7 @@
 #' @param datX0 a matrix of mandatory variables
 #' @param datProportionConst an array of cluster-specific proportions
 #'
-run_mcmc <- function(nIter, burnin, thin, n, nsamp, ninit, convex, npoint, dirichlet, proportion_model, BVS, threads, gamma_prior, gamma_sampler, eta_prior, eta_sampler, initList, rangeList, hyperparList, datEvent, datTime, datX, datX0, datProportionConst) {
-    .Call(`_GPTCM_run_mcmc`, nIter, burnin, thin, n, nsamp, ninit, convex, npoint, dirichlet, proportion_model, BVS, threads, gamma_prior, gamma_sampler, eta_prior, eta_sampler, initList, rangeList, hyperparList, datEvent, datTime, datX, datX0, datProportionConst)
+run_mcmc <- function(nIter, burnin, thin, n, nsamp, ninit, convex, npoint, dirichlet, proportion_model, BVS, beta_proposal, zeta_proposal, threads, gamma_prior, gamma_sampler, eta_prior, eta_sampler, initList, rangeList, hyperparList, datEvent, datTime, datX, datX0, datProportionConst) {
+    .Call(`_GPTCM_run_mcmc`, nIter, burnin, thin, n, nsamp, ninit, convex, npoint, dirichlet, proportion_model, BVS, beta_proposal, zeta_proposal, threads, gamma_prior, gamma_sampler, eta_prior, eta_sampler, initList, rangeList, hyperparList, datEvent, datTime, datX, datX0, datProportionConst)
 }