Package: MixtureMissing
Type: Package
Title: Robust Model-Based Clustering for Data Sets with Missing Values
        at Random
Version: 1.0.0
Authors@R: 
  c(person(given = "Hung",
           family = "Tong",
           role = c("aut", "cre"),
           email = "hungtongmx@gmail.com"),
    person(given = "Cristina",
           family = "Tortora",
           role = c("aut", "ths", "dgs"),
           email = "cristina.tortora@sjsu.edu"))
Description: Implementation of robust model based cluster analysis with missing data. 
    The models used are: Multivariate Contaminated Normal Mixtures (MCNM),
    Multivariate Student's t  Mixtures (MtM), and Multivariate Normal Mixtures (MNM)
    for data sets with missing values at random. 
    "Cluster analysis and outlier detection with missing data"
    Hung Tong, Cristina Tortora (2020) <arXiv:2012.05394>.
Imports: ContaminatedMixt (>= 1.3.4.1), mvtnorm (>= 1.1-2), mnormt (>=
        2.0.2), cluster (>= 2.1.2), rootSolve (>= 1.8.2.2), ggplot2 (>=
        3.3.5), GGally (>= 2.0.0)
Suggests: mice (>= 3.10.0)
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Repository: CRAN
RoxygenNote: 7.1.1
Depends: R (>= 3.5.0)
NeedsCompilation: no
Packaged: 2021-10-18 23:10:07 UTC; hungt
Author: Hung Tong [aut, cre],
  Cristina Tortora [aut, ths, dgs]
Maintainer: Hung Tong <hungtongmx@gmail.com>
Date/Publication: 2021-10-20 06:40:05 UTC
