Package: GridOnClusters
Type: Package
Title: Multivariate Joint Grid Discretization
Version: 0.3.2
Date: 2025-12-12
Depends: R (>= 3.5.0)
Authors@R: 
    c(person(given = "Jiandong",
             family = "Wang",
             role = "aut",
             email = "wangjd24@nmsu.edu"),
      person(given = "Sajal",
             family = "Kumar",
             role = "aut",
             email = "sajal49@nmsu.edu",
             comment = c(ORCID = "0000-0003-0930-1582")),
      person(given = "Joe",
             family = "Song",
             role = c("aut", "cre"),
             email = "joemsong@nmsu.edu",
             comment = c(ORCID = "0000-0002-6883-6547")))
Author: Jiandong Wang [aut], Sajal Kumar [aut] (ORCID:
        <https://orcid.org/0000-0003-0930-1582>), Joe Song [aut, cre]
        (ORCID: <https://orcid.org/0000-0002-6883-6547>)
Maintainer: Joe Song <joemsong@nmsu.edu>
Description: Discretize multivariate continuous data using a grid to
        capture the joint distribution that preserves clusters in
        original data. It can handle both labeled or unlabeled data.
        Both published methods (Wang et al 2020)
        <doi:10.1145/3388440.3412415> and new methods are included.
        Joint grid discretization can prepare data for model-free
        inference of association, function, or causality.
Imports: Rcpp, Ckmeans.1d.dp, cluster, fossil, dqrng, mclust, Rdpack,
        plotrix
Suggests: FunChisq, knitr, testthat (>= 2.1.0), rmarkdown
RdMacros: Rdpack
License: LGPL (>= 3)
Encoding: UTF-8
LinkingTo: BH, Rcpp
RoxygenNote: 7.3.3
NeedsCompilation: yes
VignetteBuilder: knitr
Packaged: 2026-07-11 05:14:00 UTC; root
Repository: https://cran.r-universe.dev
Date/Publication: 2025-12-12 13:40:07 UTC
RemoteUrl: https://github.com/cran/GridOnClusters
RemoteRef: HEAD
RemoteSha: 816bb0f302dd04be3315bc0949abf4013f8e41f7