Package: mixdir
Type: Package
Title: Cluster High Dimensional Categorical Datasets
Version: 0.3.0
Authors@R: c(person("Constantin", "Ahlmann-Eltze", email = "artjom31415@googlemail.com", role = c("aut", "cre"),
                    comment = c(ORCID = "0000-0002-3762-068X")),
             person("Christopher", "Yau", email="c.yau@bham.ac.uk", role="ths",
                    comment = c(ORCID = "0000-0001-7615-8523")))
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
Repository: https://const-ae.r-universe.dev
Date/Publication: 2023-09-11 18:19:37 UTC
RemoteUrl: https://github.com/const-ae/mixdir
RemoteRef: HEAD
RemoteSha: f772069f1325c8556546bdaea8c78ef29a24da9b
NeedsCompilation: yes
Packaged: 2026-06-09 07:15:57 UTC; root
Author: Constantin Ahlmann-Eltze [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-3762-068X>),
  Christopher Yau [ths] (ORCID: <https://orcid.org/0000-0001-7615-8523>)
Maintainer: Constantin Ahlmann-Eltze <artjom31415@googlemail.com>