Multivariate Joint Grid Discretization R package GridOnClusters version 0.3.2 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. Software Depends: R (>= 3.5.0) Imports: Rcpp, Ckmeans.1d.dp, cluster, fossil, dqrng, mclust, Rdpack, plotrix LinkingTo: BH, Rcpp Suggests: FunChisq, knitr, testthat (>= 2.1.0), rmarkdown Joe Song <joemsong@nmsu.edu> Comprehensive R Archive Network (CRAN) 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>) LGPL (>= 3) 2025-12-12 application/tgz https://CRAN.R-project.org/package=GridOnClusters doi:10.32614/CRAN.package.GridOnClusters