Package: MixAll
Encoding: UTF-8
Version: 1.5.1
Date: 2019-09-12
Title: Clustering and Classification using Model-Based Mixture Models
Authors@R: c(person("Serge", "Iovleff", role = c("aut","cre"), email = "Serge.Iovleff@stkpp.org")
            ,person("Parmeet", "Bathia", role = c("ctb"), email = "Bathia.Parmeet@gmail.com")
            )
Author: Serge Iovleff [aut, cre],
  Parmeet Bathia [ctb]
Maintainer: Serge Iovleff <Serge.Iovleff@stkpp.org>
Copyright: inria, University of Lille
Depends: R (>= 3.0.2), rtkore (>= 1.5.0)
Imports: methods
Description: Algorithms and methods for model-based clustering and classification.
 It supports various types of data: continuous, categorical and counting
 and can handle mixed data of these types. It can fit Gaussian (with diagonal
 covariance structure), gamma, categorical and Poisson models. The algorithms
 also support missing values. This package can be used as an independent
 alternative to the (not free) 'mixtcomp' software available at
 <https://massiccc.lille.inria.fr/>.
License: GPL (>= 2)
LinkingTo: Rcpp (>= 0.11.0), rtkore (>= 1.5.0)
SystemRequirements: GNU make
Collate: 'ClusterAlgo.R' 'ClusterAlgoPredict.R' 'ClusterInit.R'
        'ClusterStrategy.R' 'IClusterModel.R' 'ClusterModelNames.R'
        'global.R' 'ClusterCategorical.R' 'ClusterDiagGaussian.R'
        'ClusterGamma.R' 'ClusterMixedData.R' 'ClusterPlot.R'
        'ClusterPoisson.R' 'IClusterPredict.R' 'ClusterPredict.R'
        'LearnAlgo.R' 'Learners.R' 'MixAll.R' 'kmmNames.R' 'kmm.R'
        'kmmMixedData.R' 'missingValues.R'
RoxygenNote: 6.1.1
NeedsCompilation: yes
Packaged: 2019-09-12 12:21:22 UTC; iovleff
Repository: CRAN
Date/Publication: 2019-09-12 13:30:02 UTC
Built: R 3.5.3; x86_64-w64-mingw32; 2020-04-22 04:46:16 UTC; windows
Archs: i386, x64
