% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/fit_gau_em.R
\name{.fit_gau_em}
\alias{.fit_gau_em}
\title{EM algorithm for AD with missing data}
\usage{
.fit_gau_em(
  y,
  order,
  blocks = NULL,
  estimate_mu = TRUE,
  max_iter = 100,
  tol = 1e-06,
  verbose = FALSE,
  ...
)
}
\arguments{
\item{y}{Data matrix (n_subjects x n_time), may contain NA}

\item{order}{Antedependence order (0, 1, or 2)}

\item{blocks}{Block membership vector (optional)}

\item{estimate_mu}{Logical, whether to estimate mu (default TRUE)}

\item{max_iter}{Maximum number of EM iterations (default 100)}

\item{tol}{Convergence tolerance on log-likelihood (default 1e-6)}

\item{verbose}{Logical, print iteration info (default FALSE)}
}
\value{
List with fitted model (same structure as fit_gau, plus EM info)
}
\description{
Implements the EM algorithm for fitting AD(p) models with missing data
under MAR (Missing At Random) assumption.
}
\keyword{internal}
