% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{print.causalmixgpd_bundle}
\alias{print.causalmixgpd_bundle}
\title{Print a one-arm workflow bundle}
\usage{
\method{print}{causalmixgpd_bundle}(x, code = FALSE, max_code_lines = 200L, ...)
}
\arguments{
\item{x}{A \code{"causalmixgpd_bundle"} object.}

\item{code}{Logical; if TRUE, print the generated NIMBLE model code.}

\item{max_code_lines}{Integer; maximum number of code lines to print when \code{code=TRUE}.}

\item{...}{Unused.}
}
\value{
The object \code{x}, invisibly.
}
\description{
\code{print.causalmixgpd_bundle()} gives a compact structural summary of the
pre-run bundle created by \code{\link{build_nimble_bundle}}.
}
\details{
The bundle is the compiled representation of the predictive model before
MCMC. For a bulk-only fit, the underlying target law is
\deqn{f(y \mid x) = \sum_{k=1}^{K} w_k(x) f_k(y \mid x, \theta_k).}
When a GPD tail is enabled, the same bulk mixture is spliced to a generalized
Pareto tail above the threshold recorded in the bundle specification.

\code{print()} is intentionally brief. It is meant to confirm that the stored
backend, kernel, truncation size, covariate structure, and code-generation
artifacts match the intended model before you compile and sample with
\code{\link{run_mcmc_bundle_manual}}.
}
\examples{
\donttest{
y <- abs(stats::rnorm(25)) + 0.1
bundle <- build_nimble_bundle(y = y, backend = "sb", kernel = "normal",
                             GPD = FALSE, components = 3)
print(bundle)
print(bundle, code = TRUE, max_code_lines = 30)
}
}
\seealso{
\code{\link{summary.causalmixgpd_bundle}}, \code{\link{mcmc}},
\code{\link{run_mcmc_bundle_manual}}.
}
