% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/batch-means.R
\name{batch_means_ci}
\alias{batch_means_ci}
\title{Pooled Batch-Means Confidence Intervals from Multiple Chains}
\usage{
batch_means_ci(
  chain_trajectories,
  level = 0.95,
  alpha = 0.501,
  M = NULL,
  N = NULL,
  drop_burnin = TRUE,
  burnin_iter = 0
)
}
\arguments{
\item{chain_trajectories}{list of numeric matrices, each with rows = iterations
and columns = parameters.}

\item{level}{confidence level.}

\item{alpha}{stepsize decay exponent in \eqn{(1/2, 1)}.}

\item{M}{number of retained batches per chain (excluding burn-in batch 0).}

\item{N}{decorrelation constant used in the batch boundary formula.}

\item{drop_burnin}{logical; if `TRUE`, discard batch 0.}

\item{burnin_iter}{non-negative integer. Explicitly discard the first
`burnin_iter` iterations of each chain before Xi-style batching.}
}
\value{
A list with pooled estimates, covariance, standard errors, and
confidence intervals.
}
\description{
Compute pooled point estimates, covariance, and Wald confidence intervals from
multiple chain trajectories.
}
