BayesSurvive (version 0.0.2)

func_MCMC: Function to run MCMC sampling

Description

This an internal function for MCMC sampling

Usage

func_MCMC(
  survObj,
  hyperpar,
  initial,
  nIter,
  thin,
  burnin,
  S,
  method,
  MRF_2b,
  MRF_G,
  output_graph_para,
  verbose
)

Value

A list object saving the MCMC results with components including 'gamma.p', 'beta.p', 'h.p', 'gamma.margin', 'beta.margin', 's', 'eta0', 'kappa0', 'c0', 'pi.ga', 'tau', 'cb', 'accept.RW', 'log.jpost', 'log.like', 'post.gamma'

Arguments

survObj

a list containing observed data from n subjects; t, di, X. See details for more information

hyperpar

a list containing prior parameter values

initial

a list containing prior parameters' initial values

nIter

the number of iterations of the chain

thin

thinning MCMC intermediate results to be stored

burnin

number of iterations to discard at the start of the chain. Default is 0

S

the number of subgroups

method

a method option from c("Pooled", "CoxBVSSL", "Sub-struct")

MRF_2b

two different b in MRF prior for subgraphs G_ss and G_rs

MRF_G

logical value. MRF_G = TRUE is to fix the MRF graph which is provided in the argument hyperpar, and MRF_G = FALSE is to use graphical model for leanring the MRF graph

output_graph_para

allow (TRUE) or suppress (FALSE) the output for parameters 'G', 'V', 'C' and 'Sig' in the graphical model if MRF_G = FALSE

verbose

logical value to display the progess of MCMC