% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{print.causalmixgpd_qte}
\alias{print.causalmixgpd_qte}
\title{Print a QTE-style effect object}
\usage{
\method{print}{causalmixgpd_qte}(x, digits = 3, max_rows = 6, ...)
}
\arguments{
\item{x}{A \code{"causalmixgpd_qte"} object from \code{qte()}.}

\item{digits}{Number of digits to display.}

\item{max_rows}{Maximum number of estimate rows to display.}

\item{...}{Unused.}
}
\value{
The object \code{x}, invisibly.
}
\description{
\code{print.causalmixgpd_qte()} prints a compact summary for objects produced
by \code{\link{qte}}, \code{\link{qtt}}, or \code{\link{cqte}}.
}
\details{
These objects store posterior summaries of quantile treatment contrasts. In
the marginal case,
\deqn{\Delta(\tau) = Q_{Y^1}(\tau) - Q_{Y^0}(\tau).}
For \code{qtt()}, the same contrast is standardized to the treated covariate
distribution, and for \code{cqte()} it is evaluated conditionally at the supplied
covariate profiles.

The print method is intentionally compact: it reports the prediction setup and
the resulting effect table, but it does not attempt to reproduce all
posterior draws. Use \code{summary()} or \code{plot()} on the same object for more
structured reporting.
}
\examples{
\donttest{
N <- 25
X <- data.frame(x1 = stats::rnorm(N))
A <- stats::rbinom(N, 1, 0.5)
y <- abs(stats::rnorm(N)) + 0.1
mcmc_small <- list(niter = 100, nburnin = 50, thin = 1, nchains = 1, seed = 1)
cb <- build_causal_bundle(y = y, X = X, A = A, backend = "sb", kernel = "normal",
                         components = 3, mcmc_outcome = mcmc_small, mcmc_ps = mcmc_small)
fit <- run_mcmc_causal(cb, show_progress = FALSE)
q <- qte(fit, probs = c(0.25, 0.5, 0.75), interval = "credible")
print(q)
}
}
\seealso{
\code{\link{summary.causalmixgpd_qte}},
\code{\link{plot.causalmixgpd_qte}}, \code{\link{qte}},
\code{\link{cqte}}.
}
