Package: pecme
Type: Package
Title: Penalized ECME Estimation for Censored Linear Mixed Models
Version: 0.1.1
Authors@R: c(
      person(
        "Ali Asghar",
        "Haeri-Mehrizi",
        email = "haeri.stat@gmail.com",
        role = c("aut", "cre")
      ),
      person(
        "Arshia",
        "Haeri-Mehrizi",
        email = "haeri.arshia@gmail.com",
        role = "aut"
      ),
      person(
        "Adel",
        "Mohammadpour",
        email = "adel.mohammadpour@ucalgary.ca",
        role = "rev"
      )
    )
Description: Fits Gaussian linear mixed models with a random intercept
        when the response is subject to left, right, and/or interval
        censoring, using the Expectation/Conditional Maximization
        Either (ECME) algorithm of Liu and Rubin (1994) in the spirit
        of the fast censored-response mixed-model algorithm of Vaida
        and Liu (2009). Simultaneous estimation and variable selection
        is supported through coordinate-descent penalized maximization
        with Lasso, Adaptive Lasso, SCAD, MCP, Elastic Net, and Ridge
        penalties (no penalty is also supported). The random intercept
        is integrated out by Gauss-Hermite quadrature at every
        iteration, and the two ECME conditional-maximization steps
        respectively maximize the expected penalized complete-data
        objective (for the regression coefficients) and the actual
        observed-data marginal likelihood (for the variance
        components), which is the defining feature of ECME relative to
        plain ECM/EM. The package provides a single-fit engine, a
        sequential/parallel penalty-parameter grid search with
        information-criterion or cross-validated selection,
        data-dependent or user-supplied lambda grids, and an
        Expectation-Maximization based treatment of a completely
        missing (at random) response, sharing the same truncated-normal
        machinery used for censoring. References: Liu and Rubin (1994)
        "The ECME algorithm: A simple extension of EM and ECM with
        faster monotone convergence" <doi:10.1093/biomet/81.4.633>;
        Vaida and Liu (2009) "Fast Implementation for Normal Mixed
        Effects Models With Censored Response"
        <doi:10.1198/jcgs.2009.07130>.
License: MIT + file LICENSE
Encoding: UTF-8
Depends: R (>= 4.1.0)
Imports: stats, graphics, parallel, lme4, withr
Suggests: testthat (>= 3.0.0), waldo, mice
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-10-08 11:45:20 UTC; root
Author: Ali Asghar Haeri-Mehrizi [aut, cre], Arshia Haeri-Mehrizi
        [aut], Adel Mohammadpour [rev]
Maintainer: Ali Asghar Haeri-Mehrizi <haeri.stat@gmail.com>
Config/pak/sysreqs: cmake make
Repository: https://haeristat.r-universe.dev
Date/Publication: 2026-10-07 09:00:08 UTC
RemoteUrl: https://github.com/cran/pecme
RemoteRef: HEAD
RemoteSha: 37c38857f11e4da27dfd1c05c48762e219bef329