Note: -*- Encoding: utf-8 -*-
Package: stepmixr
Type: Package
Title: Interface to 'Python' Package 'StepMix'
Version: 0.1.3
Date: 2025-07-04
Authors@R: c(
   person("Éric", "Lacourse", role="aut"),
   person("Roxane", "de la Sablonnière", role="aut"),
   person("Charles-Édouard", "Giguère", role=c("aut", "cre"),
      email = "ce.giguere@gmail.com"),
   person("Sacha", "Morin", role="aut"),	
   person("Robin", "Legault", role="aut"),
   person("Félix", "Laliberté", role = "aut"),
   person("Zsusza", "Bakk", role="ctb") )   
Author: Éric Lacourse [aut], Roxane de la Sablonnière [aut],
        Charles-Édouard Giguère [aut, cre], Sacha Morin [aut], Robin
        Legault [aut], Félix Laliberté [aut], Zsusza Bakk [ctb]
Maintainer: Charles-Édouard Giguère <ce.giguere@gmail.com>
Depends: R (>= 4.0.0)
Imports: reticulate (>= 1.8)
Description: This is an interface for the 'Python' package 'StepMix'.
        It is a 'Python' package following the scikit-learn API for
        model-based clustering and generalized mixture modeling (latent
        class/profile analysis) of continuous and categorical data.
        'StepMix' handles missing values through Full Information
        Maximum Likelihood (FIML) and provides multiple stepwise
        Expectation-Maximization (EM) estimation methods based on
        pseudolikelihood theory. Additional features include support
        for covariates and distal outcomes, various simulation
        utilities, and non-parametric bootstrapping, which allows
        inference in semi-supervised and unsupervised settings.
        Software paper available at <doi:10.18637/jss.v113.i08>.
License: GPL-2
Encoding: UTF-8
LazyLoad: TRUE
URL: https://github.com/Labo-Lacourse/StepMixr
NeedsCompilation: no
Config/pak/sysreqs: libpng-dev python3
Repository: https://labo-lacourse.r-universe.dev
Date/Publication: 2025-07-28 04:25:11 UTC
RemoteUrl: https://github.com/labo-lacourse/stepmixr
RemoteRef: HEAD
RemoteSha: ad7781fe2ac580f754d3341210a10fcc95c83a76
Packaged: 2026-09-18 08:30:14 UTC; root