dot-logL_gau_missing: Compute observed-data log-likelihood for AD with missing...

In antedep: Antedependence Models for Longitudinal Data

Compute observed-data log-likelihood for AD with missing values

Description

Uses multivariate normal marginalization to compute the likelihood of observed values, marginalizing over missing values.

Usage

.logL_gau_missing(y, order, mu, phi, sigma, blocks = NULL, tau = 0)

Arguments

y	Data matrix (n_subjects x n_time), may contain NA
order	Antedependence order (0, 1, or 2)
mu	Mean vector (length n_time)
phi	Dependence parameter(s)
sigma	Innovation standard deviations (length n_time)
blocks	Block membership vector (optional)
tau	Block effects, first element constrained to zero

Value

Observed-data log-likelihood (scalar)

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