em_gau: EM algorithm for Gaussian AD model estimation

In antedep: Antedependence Models for Longitudinal Data

EM algorithm for Gaussian AD model estimation

Description

Convenience wrapper around fit_gau with na_action = "em" to provide a parallel entry point to em_inad.

Usage

em_gau(
  y,
  order = 1,
  blocks = NULL,
  estimate_mu = TRUE,
  max_iter = 100,
  tol = 1e-06,
  verbose = FALSE,
  ...
)

Arguments

y	Numeric matrix (n_subjects x n_time), may contain NA.
order	Integer 0, 1, or 2.
blocks	Optional vector of block membership (length n_subjects).
estimate_mu	Logical, whether to estimate mu (default TRUE).
max_iter	Maximum EM iterations.
tol	EM convergence tolerance.
verbose	Logical, print EM progress.
...	Additional arguments passed to fit_gau.

Details

This is an alias-style helper for users who prefer explicit em_* entry points across model families.

Value

An gau_fit object as returned by fit_gau.

See Also

fit_gau, em_inad, em_cat, fit_cat

Examples

set.seed(1)
y <- simulate_gau(n_subjects = 35, n_time = 5, order = 1, phi = 0.3)
y[sample(length(y), 8)] <- NA
fit <- em_gau(y, order = 1, max_iter = 20, tol = 1e-5)
fit$settings$na_action

antedep documentation built on April 25, 2026, 1:06 a.m.