% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bayes_approx.R
\name{bayes_gibbs_censored}
\alias{bayes_gibbs_censored}
\title{Bayesian Inference via Gibbs Sampling for Censored Data Models}
\usage{
bayes_gibbs_censored(log_posterior, init_par, n_sim = 5000, burn_in = 1000)
}
\arguments{
\item{log_posterior}{Function taking parameter vector and returning log posterior density.}

\item{init_par}{Initial parameter vector.}

\item{n_sim}{Total number of MCMC iterations.}

\item{burn_in}{Number of initial iterations to discard as burn-in.}
}
\value{
S3 object of class \code{bayes_fit} with parameter chains, posterior means, and credible intervals.
}
\description{
Bayesian Inference via Gibbs Sampling for Censored Data Models
}
\examples{
log_post <- function(th) {
  if (th[1] <= 0) return(-Inf)
  dexp(th[1], rate = 1, log = TRUE) +
    sum(dexp(c(0.5, 1.2, 0.8), rate = th[1], log = TRUE))
}
bayes_gibbs_censored(
  log_post, init_par = c(1.0),
  n_sim = 1000, burn_in = 200
)
}
