Package: mixdir
Type: Package
Title: Cluster High Dimensional Categorical Datasets
Version: 0.2.0
Authors@R: c(person("Constantin", "Ahlmann-Eltze", email = "artjom31415@googlemail.com", role = c("aut", "cre")),
             person("Christopher", "Yau", email="c.yau@bham.ac.uk", role="ths"))
Description: Scalable Bayesian clustering of categorical datasets. The package implements a hierarchical Dirichlet 
    (Process) mixture  of multinomial distributions. It is thus a probabilistic latent class model (LCM) and can be used
    to reduce the  dimensionality of hierarchical data and cluster individuals into latent classes. It can automatically
    infer an appropriate number of latent classes or find k classes, as defined by the user.  The model is based on a
    paper by Dunson and Xing (2009) <doi:10.1198/jasa.2009.tm08439>, but implements a scalable variational inference algorithm so that it is
    applicable to large datasets. It is described and tested in the accompanying paper by 
    Ahlmann-Eltze and Yau (2018) <doi:10.1109/DSAA.2018.00068>.
URL: https://github.com/const-ae/mixdir
License: GPL-3
Encoding: UTF-8
LazyData: true
Suggests: testthat, tibble, purrr, dplyr, rmutil, pheatmap, mcclust,
        ggplot2, tidyr, utils
RoxygenNote: 6.1.1
Imports: extraDistr, Rcpp
Depends: R (>= 2.10)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2019-03-11 17:14:06 UTC; constantin
Author: Constantin Ahlmann-Eltze [aut, cre],
  Christopher Yau [ths]
Maintainer: Constantin Ahlmann-Eltze <artjom31415@googlemail.com>
Repository: CRAN
Date/Publication: 2019-03-11 20:40:09 UTC
