Package: SSLfmm
Type: Package
Title: Semi-Supervised Learning with Mixed Missingness in Finite
        Mixture Models
Version: 0.2.0
Depends: R (>= 3.6.0)
Authors@R: c(
    person("Geoffrey J.", "McLachlan", role = "aut",
           email = "g.mclachlan@uq.edu.au",
           comment = c(ORCID = "0000-0002-5921-3145")),
    person("Jinran", "Wu", role = c("aut", "cre"),
           email = "jinran.wu@uq.edu.au",
           comment = c(ORCID = "0000-0002-2388-3614"))
    )
Description: Semi-supervised Gaussian finite mixture models for partially labelled data
    under complete-case, missing completely at random (MCAR), entropy-dependent missing
    at random (MAR), and mixed MCAR/MAR label-missingness formulations. For the mixed
    formulation, the source of a missing label may be observed or latent. The package
    supports equal and component-specific covariance matrices, model fitting, simulation,
    initialization, prediction, classification performance assessment, and entropy-based
    diagnostics. A semi-synthetic Blood Transfusion data set is included to illustrate the
    applied workflow.
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: graphics, stats
Suggests: testthat (>= 3.0.0)
Config/testthat/edition: 3
Config/roxygen2/version: 8.0.0
NeedsCompilation: no
Packaged: 2026-08-19 01:22:01 UTC; uqjwu15
Author: Geoffrey J. McLachlan [aut] (ORCID:
    <https://orcid.org/0000-0002-5921-3145>),
  Jinran Wu [aut, cre] (ORCID: <https://orcid.org/0000-0002-2388-3614>)
Maintainer: Jinran Wu <jinran.wu@uq.edu.au>
Repository: CRAN
Date/Publication: 2026-08-20 12:02:04 UTC
