% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/wrappers.R
\name{mcmc}
\alias{mcmc}
\title{Run posterior sampling from a prepared bundle}
\usage{
mcmc(b, ...)
}
\arguments{
\item{b}{A non-causal or causal bundle.}

\item{...}{Optional MCMC overrides (\code{niter}, \code{nburnin}, \code{thin},
\code{nchains}, \code{seed}, \code{waic}) and runner controls
(\code{show_progress}, \code{quiet}).}
}
\value{
A fitted object of class \code{"mixgpd_fit"} or
\code{"causalmixgpd_causal_fit"}.
}
\description{
\code{mcmc()} is the generic workflow runner. It dispatches to
\code{\link{run_mcmc_bundle_manual}} for one-arm bundles and to
\code{\link{run_mcmc_causal}} for causal bundles.
}
\details{
This wrapper is useful when you want a two-stage workflow:
build first, inspect or modify the bundle, then sample. Named MCMC arguments
supplied through \code{...} override the settings stored in the bundle before
execution.

The returned fit represents posterior draws from the finite SB/CRP
approximation encoded in the bundle. Downstream summaries therefore target
posterior predictive quantities such as \eqn{f(y \mid x)},
\eqn{F(y \mid x)}, and derived treatment-effect functionals.
}
\seealso{
\code{\link{bundle}}, \code{\link{run_mcmc_bundle_manual}},
\code{\link{run_mcmc_causal}}, \code{\link{predict.mixgpd_fit}}.
}
