% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/batch-means.R
\name{ngme_batch_ci}
\alias{ngme_batch_ci}
\title{Batch-Means Confidence Intervals from an ngme Fit}
\usage{
ngme_batch_ci(
  ngme,
  name = "all",
  level = 0.95,
  alpha = 0.501,
  M = NULL,
  N = NULL,
  apply_transform = TRUE,
  drop_burnin = TRUE,
  burnin_iter = 0
)
}
\arguments{
\item{ngme}{fitted `ngme` object with `store_traj = TRUE` during optimization.}

\item{name}{either `"all"` (default) to use all parameters jointly, a latent
model name, or `"general"` for measurement-noise/fixed-effect block.}

\item{level}{confidence level.}

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

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

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

\item{apply_transform}{logical; if `TRUE`, inference is first computed in the
raw optimization space and then mapped to user scale via post-hoc Delta
method (Post-delta).}

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

\item{burnin_iter}{non-negative integer. Explicitly discard the first
`burnin_iter` optimization iterations before Xi-style batching.}
}
\value{
Same structure as [batch_means_ci()] with extra metadata fields
`name` and `apply_transform`.
}
\description{
Compute Xi-style batch-means confidence intervals directly from trajectories
stored in an `ngme` object.
}
