\name{inter_bootstrap}
\alias{inter_bootstrap}
\alias{print.inter_bootstrap}
\alias{decompose_uncertainty}
\title{Bootstrap and Summarize Uncertainty}
\usage{
inter_bootstrap(object, R = 199L,
  type = c("multiplier", "replicate"), seed = 123,
  level = 0.95, progress = FALSE)

decompose_uncertainty(object, bootstrap = NULL, bounds = NULL)

\method{print}{inter_bootstrap}(x, ...)
}
\arguments{
\item{object}{A fitted \code{inter_sae} object.}
\item{R}{Number of bootstrap replicates.}
\item{type}{Multiplier or supplied-replicate-weight bootstrap.}
\item{seed}{Random seed for multiplier bootstrap.}
\item{level}{Confidence level.}
\item{progress}{Print periodic progress messages.}
\item{bootstrap}{Optional result from \code{inter_bootstrap()}.}
\item{bounds}{Optional result from \code{identification_bounds()}.}
\item{x}{Object to print.}
\item{...}{Unused.}
}
\value{
\code{inter_bootstrap()} returns an \code{inter_bootstrap} object containing a
summary and replicate matrix. \code{decompose_uncertainty()} returns a data
frame.
}
\description{
Refit population reconstruction and the outcome model under each set of
weights. Standard errors include sampling and refitting variation.
Identification width can be reported separately.
}
\examples{
\dontrun{
example_data <- inter_example()
design <- inter_design(example_data$survey, "weight", "area", "strata", "psu")
margins <- census_margins(example_data$margins)
fit <- fit_inter_sae(unemployed ~ sex + age + residence + area,
  design, margins, family = "binomial")
boot <- inter_bootstrap(fit, R = 99)
boot
}
}
