Package: EMMIXSSL
Type: Package
Title: Semi-Supervised Gaussian Mixture Model with a Missing-Data
        Mechanism
Version: 1.1.1
Author: Ziyang Lyu, Daniel Ahfock, Geoffrey J. McLachlan
Maintainer: Ziyang Lyu <ziyang.lyu@unsw.edu.au>
Description: The algorithm of semi-supervised learning based on finite
        Gaussian mixture models with a missing-data mechanism is
        designed for a fitting g-class Gaussian mixture model via
        maximum likelihood (ML). It is proposed to treat the labels of
        the unclassified features as missing-data and to introduce a
        framework for their missing as in the pioneering work of Rubin
        (1976) for missing in incomplete data analysis. This dependency
        in the missingness pattern can be leveraged to provide
        additional information about the optimal classifier as
        specified by Bayes’ rule.
Depends: R (>= 3.1.0), mvtnorm,stats
License: GPL-3
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.0
NeedsCompilation: no
Packaged: 2026-07-10 08:51:43 UTC; root
Repository: https://lyu9118.r-universe.dev
Date/Publication: 2022-10-18 11:17:58 UTC
RemoteUrl: https://github.com/cran/EMMIXSSL
RemoteRef: HEAD
RemoteSha: cfacc7d02e6d654c0664105ad0a0dbe9573c592d