% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/diagnostics.R
\name{gpci_impsam}
\alias{gpci_impsam}
\title{High-Level User Interface Function for Importance Sampling GPCIs}
\usage{
gpci_impsam(
  data,
  pdf = NULL,
  cdf = NULL,
  sf = NULL,
  prior = NULL,
  chain_length = 1000,
  burn_in = 200,
  thinning = 1,
  USL,
  LSL,
  target = (USL + LSL)/2,
  indices = NULL
)
}
\arguments{
\item{data}{Numeric vector of process observations.}

\item{pdf}{Custom PDF/PMF function \code{function(x, ...)}.}

\item{cdf}{Custom CDF function \code{function(x, ...)}.}

\item{sf}{Custom Survival Function \code{function(x, ...)}.}

\item{prior}{Prior distribution hyperparameters list or log-prior function.}

\item{chain_length}{MCMC chain length (default 1000).}

\item{burn_in}{MCMC burn-in iterations (default 200).}

\item{thinning}{Thinning interval (default 1).}

\item{USL}{Upper Specification Limit.}

\item{LSL}{Lower Specification Limit.}

\item{target}{Target process value.}

\item{indices}{GPCI names to evaluate.}
}
\value{
A list of class \code{"gpciImpSam"} with full summary results.
}
\description{
Main user interface to fit uncensored data under Importance Sampling and evaluate GPCIs,
returning point estimates, parameter chains, GPCI chains, HPD intervals, and convergence diagnostics.
}
\examples{
gpci_impsam(
  data = rnorm(50, 10, 1),
  pdf = function(x, mean = 0, sd = 1) dnorm(x, mean, sd),
  cdf = function(x, mean = 0, sd = 1) pnorm(x, mean, sd),
  chain_length = 300, burn_in = 50,
  USL = 13, LSL = 7
)
}
