Package: multimix
Type: Package
Title: Fit Mixture Models Using the Expectation Maximisation (EM)
        Algorithm
Version: 1.0-11
Date: 2023-01-28
Authors@R: c(
    person("Murray", "Jorgensen", , "majmurr@gmail.com", role = "aut"),
    person("James", "Curran", , "j.curran@auckland.ac.nz", role = c("cre", "ctb"))
  )
Description: A set of functions which use the Expectation Maximisation
        (EM) algorithm (Dempster, A. P., Laird, N. M., and Rubin, D. B.
        (1977) <doi:10.1111/j.2517-6161.1977.tb01600.x> Maximum
        likelihood from incomplete data via the EM algorithm, Journal
        of the Royal Statistical Society, 39(1), 1--22) to take a
        finite mixture model approach to clustering. The package is
        designed to cluster multivariate data that have categorical and
        continuous variables and that possibly contain missing values.
        The method is described in Hunt, L. and Jorgensen, M. (1999)
        <doi:10.1111/1467-842X.00071> Australian & New Zealand Journal
        of Statistics 41(2), 153--171 and Hunt, L. and Jorgensen, M.
        (2003) <doi:10.1016/S0167-9473(02)00190-1> Mixture model
        clustering for mixed data with missing information,
        Computational Statistics & Data Analysis, 41(3-4), 429--440.
Depends: mvtnorm, R (>= 4.0.0)
Encoding: UTF-8
Imports: methods, Rcpp (>= 1.0.10)
LazyData: true
License: GPL (>= 2)
LinkingTo: Rcpp
URL: https://github.com/jmcurran/multimix
BugReports: https://github.com/jmcurran/multimix/issues
RoxygenNote: 7.2.3
Repository: https://jmcurran.r-universe.dev
Date/Publication: 2023-01-31 21:09:23 UTC
RemoteUrl: https://github.com/jmcurran/multimix
RemoteRef: HEAD
RemoteSha: bacd1417c37c772279c5cb3774904ac805170110
NeedsCompilation: yes
Packaged: 2026-06-07 10:00:38 UTC; root
Author: Murray Jorgensen [aut],
  James Curran [cre, ctb]
Maintainer: James Curran <j.curran@auckland.ac.nz>