Package: gmmsslm
Type: Package
Title: Semi-Supervised Gaussian Mixture Model with a Missing-Data
        Mechanism
Version: 1.1.6
Authors@R: c(person("Ziyang Lyu", role = c("aut", "cre"), email = "ziyang.lyu@unsw.edu.au"),person("Daniel Ahfock", role = "aut"),person("Ryan Thompson", role = "aut"),person("Geoffrey J. McLachlan", role = "aut"))
Description: The algorithm of semi-supervised learning is based on
        finite Gaussian mixture models and includes a mechanism for
        handling missing data. It aims to fit a g-class Gaussian
        mixture model using maximum likelihood. The algorithm treats
        the labels of unclassified features as missing data, building
        on the framework introduced by Rubin (1976)
        <doi:10.2307/2335739> for missing data analysis. By taking into
        account the dependencies in the missing pattern, the algorithm
        provides more information for determining the optimal
        classifier, as specified by Bayes' rule.
Depends: R (>= 3.1.0), mvtnorm,stats,methods
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.3
NeedsCompilation: no
Packaged: 2026-06-18 11:16:50 UTC; root
Author: Ziyang Lyu [aut, cre], Daniel Ahfock [aut], Ryan Thompson
        [aut], Geoffrey J. McLachlan [aut]
Maintainer: Ziyang Lyu <ziyang.lyu@unsw.edu.au>
Repository: https://lyu9118.r-universe.dev
Date/Publication: 2025-04-17 04:20:02 UTC
RemoteUrl: https://github.com/cran/gmmsslm
RemoteRef: HEAD
RemoteSha: 16668b092909cbe274c40e54f4f5523ef8215224