% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{summary.CausalShrinkageForest}
\alias{summary.CausalShrinkageForest}
\title{Summarise a CausalShrinkageForest model}
\usage{
\method{summary}{CausalShrinkageForest}(object, bayesian_bootstrap = TRUE, ...)
}
\arguments{
\item{object}{A fitted \code{CausalShrinkageForest} model object.}

\item{bayesian_bootstrap}{Logical; if \code{TRUE} (default), the ATE
posterior is computed by reweighting the per-iteration CATE vector with
Dirichlet(1, ..., 1) weights (Bayesian bootstrap). This gives a draw from
the posterior of the \emph{population} ATE (PATE), with a credible
interval that accounts for uncertainty in the covariate distribution. If
\code{FALSE}, equal \eqn{1/n} weights are used, giving the mixed ATE
(MATE), which conditions on the observed covariates. Ignored when
posterior samples are not stored.}

\item{...}{Currently unused.}
}
\value{
A \code{summary.CausalShrinkageForest} object with elements:
\describe{
\item{call}{The original model call.}
\item{outcome_type}{Outcome type.}
\item{timescale}{Timescale for survival outcomes.}
\item{prior}{Prior specification for control and treatment forests.}
\item{mcmc}{MCMC settings.}
\item{data_info}{Training and test data dimensions.}
\item{treatment_effect}{List with \code{ate} (posterior mean ATE),
\code{cate_sd} (SD of individual CATEs), and optionally
\code{ate_lower}, \code{ate_upper} (95 percent credible interval;
requires \code{store_posterior_sample = TRUE}) and
\code{bayesian_bootstrap} (the flag used to produce the CI).}
\item{prognostic}{Summary of the prognostic function (mean, SD, range).}
\item{sigma}{Named vector with posterior mean, SD, and 95 percent
credible interval of sigma (if estimated).}
\item{variable_importance_control}{Variable importance for the control
forest (if available).}
\item{variable_importance_treat}{Variable importance for the treatment
forest (if available).}
\item{acceptance_ratios}{List with acceptance ratios for each forest.}
}
}
\description{
Returns an inspectable list with treatment effect estimates, prognostic
function summaries, posterior sigma, variable importance for each forest,
and MCMC diagnostics.
}
\seealso{
\code{\link{print.summary.CausalShrinkageForest}},
\code{\link{CausalHorseForest}}, \code{\link{CausalShrinkageForest}}
}
