Package: GMMinit
Type: Package
Title: Optimal Initial Value for Gaussian Mixture Model
Date: 2026-01-20
Authors@R: c(person("Jing", "Li", 
             email = "jli178@crimson.ua.edu", role = c("aut", "cre")),
            person("Yana", "Melnykov",
             email = "ymelnykov@ua.edu", role = "aut"))
Version: 1.0.0
Maintainer: Jing Li <jli178@crimson.ua.edu>
Author: Jing Li [aut, cre], Yana Melnykov [aut]
Description: Generating, evaluating, and selecting initialization
        strategies for Gaussian Mixture Models (GMMs), along with
        functions to run the Expectation-Maximization (EM) algorithm.
        Initialization methods are compared using log-likelihood, and
        the best-fitting model can be selected using BIC. Methods build
        on initialization strategies for finite mixture models
        described in Michael and Melnykov (2016)
        <doi:10.1007/s11634-016-0264-8> and Biernacki et al. (2003)
        <doi:10.1016/S0167-9473(02)00163-9>, and on the EM algorithm of
        Dempster et al. (1977)
        <doi:10.1111/j.2517-6161.1977.tb01600.x>. Background on
        model-based clustering includes Fraley and Raftery (2002)
        <doi:10.1198/016214502760047131> and McLachlan and Peel (2000,
        ISBN:9780471006268).
License: GPL (>= 2)
Encoding: UTF-8
ByteCompile: true
Imports: mvtnorm, mclust, mvnfast, stats
Config/testthat/edition: 3
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2026-06-23 08:39:08 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2026-01-24 10:40:07 UTC
RemoteUrl: https://github.com/cran/GMMinit
RemoteRef: HEAD
RemoteSha: a5e5a163be124dedcbacb6b6751b8832372b3773