% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/pit.R
\name{pit_values}
\alias{pit_values}
\alias{pit_values.default}
\alias{pit_values.dcvar_hmm_fit}
\alias{pit_values.dcvar_model_fit}
\alias{pit_values.dcvar_tv_fit}
\title{Extract PIT values from a fitted model}
\usage{
pit_values(object, ...)

\method{pit_values}{default}(object, ...)

\method{pit_values}{dcvar_hmm_fit}(object, ...)

\method{pit_values}{dcvar_model_fit}(object, ...)

\method{pit_values}{dcvar_tv_fit}(object, ...)
}
\arguments{
\item{object}{A fitted model object.}

\item{...}{Additional arguments (unused).}
}
\value{
A data frame with columns \code{time}, \code{variable}, \code{pit}.
}
\description{
Computes approximate Probability Integral Transform values using posterior
mean residuals and posterior mean margin parameters. Large departures from
uniformity can indicate model misfit, but these are not exact posterior
predictive PIT values.
}
\details{
PIT values are computed from posterior mean residuals and posterior mean
margin parameters. Treat them as a fast plug-in diagnostic rather than an
exact posterior predictive transform that integrates over full posterior
uncertainty. PIT diagnostics are currently implemented for the three core
single-level fit classes only.
}
