% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/bootstrap.R
\name{boot_ci_censor}
\alias{boot_ci_censor}
\alias{gpci_boot_censor}
\alias{print.gpci_ci_censor}
\alias{summary.gpci_ci_censor}
\title{Compute Bootstrap Confidence Intervals for Process Capability Indices (Interval-Censored Data)}
\usage{
boot_ci_censor(
  fit,
  B = 2000,
  alpha = c(0.1, 0.05, 0.01),
  method = c("percentile", "normal", "basic", "BCa", "BCp", "studentized"),
  type = c("parametric", "nonparametric"),
  parallel = FALSE,
  ncpus = 1
)

gpci_boot_censor(
  fit,
  B = 2000,
  alpha = c(0.1, 0.05, 0.01),
  method = c("percentile", "normal", "basic", "BCa", "BCp", "studentized"),
  type = c("parametric", "nonparametric"),
  parallel = FALSE,
  ncpus = 1
)

\method{print}{gpci_ci_censor}(x, ...)

\method{summary}{gpci_ci_censor}(object, ...)
}
\arguments{
\item{fit}{A \code{gpcifit_censor} object returned by \code{\link{capability_censor}}.}

\item{B}{Number of bootstrap replicates.}

\item{alpha}{Vector of significance levels (default is 0.10, 0.05, 0.01).}

\item{method}{Confidence interval method ("percentile", "normal", "basic", "BCa", "BCp", "studentized").}

\item{type}{Bootstrap type ("parametric" or "nonparametric").}

\item{parallel}{Logical. If TRUE, parallel processing is used.}

\item{ncpus}{Number of CPUs for parallel execution.}

\item{x, object}{An object of class \code{gpci_ci_censor}.}

\item{...}{Additional print/summary arguments.}
}
\value{
An object of class \code{gpci_ci_censor}.
}
\description{
Runs parametric or non-parametric bootstrapping to compute confidence intervals
for generalized process capability indices at multiple significance levels (90\%, 95\%, 99\%)
under interval-censored data.
}
\examples{
\donttest{
dist_norm <- dist_normal()
left <- c(9.5, 10.2, 8.8, 11.1, 9.9)
right <- c(10.5, 11.2, 9.8, 12.1, 10.9)
fit <- capability_censor(left, right, dist_norm, USL = 13, LSL = 7)
ci <- boot_ci_censor(fit, B = 100, alpha = c(0.10, 0.05, 0.01), method = "percentile")
print(ci)
}
}
