run_mcmc: Main function implemented in C++ for the MCMC loop

Description

Main function implemented in C++ for the MCMC loop

Usage

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
)

Arguments

nIter: number of MCMC iterations
burnin: length of MCMC burn-in period
thin: number of thinning
n: number of samples to draw
nsamp: how many samples to draw for generating each sample; only the last draw will be kept
ninit: number of initials as meshgrid values for envelop search
convex: adjustment for convexity (non-negative value, default 1.0)
npoint: maximum number of envelope points
dirichlet: not yet implemented
proportion_model: logical value for modeling the proportions data
BVS: logical value for implementing Bayesian variable selection
threads: maximum threads used for parallelization. Default is 1
gamma_prior: one of c("bernoulli", "MRF")
gamma_sampler: one of c("mc3", "bandit")
eta_prior: one of c("bernoulli", "MRF")
eta_sampler: one of c("mc3", "bandit")
initList: a list of initial values for parameters "kappa", "xi", "betas", and "zetas"
rangeList: a list of ranges of initial values for parameters "kappa", "xi", "betas", and "zetas"
hyperparList: a list of relevant hyperparameters
datEvent: a vector of survival status
datTime: a vector of survival times
datX: an array of cluster-specific covariates
datX0: a matrix of mandatory variables
datProportionConst: an array of cluster-specific proportions