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
Repository: CRAN
ByteCompile: true
Imports: mvtnorm, mclust, mvnfast, stats
Config/testthat/edition: 3
RoxygenNote: 7.3.1
NeedsCompilation: no
Packaged: 2026-01-20 16:33:01 UTC; jingli
Date/Publication: 2026-01-24 10:40:07 UTC
Built: R 4.6.0; ; 2026-04-25 19:18:39 UTC; unix
