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GridOnClusters: Cluster-Preserving Multivariate Joint Grid Discretization
Discretize multivariate continuous data using a grid to capture the
joint distribution that preserves clusters in original data (Wang et al 2020)
<doi:10.1145/3388440.3412415>. It can handle both labeled or unlabeled data.
Joint grid discretization can prepare data for model-free inference of
association, function, or causality.
| Version: |
0.4.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, Ckmeans.1d.dp, cluster, fossil, dqrng, mclust, Rdpack, plotrix |
| LinkingTo: |
BH, Rcpp, RcppArmadillo |
| Suggests: |
FunChisq, knitr, testthat (≥ 2.1.0), rmarkdown |
| Published: |
2026-07-18 |
| DOI: |
10.32614/CRAN.package.GridOnClusters |
| Author: |
Jiandong Wang 
[aut],
Sajal Kumar [aut],
Joe Song [aut,
cre] |
| Maintainer: |
Joe Song <joemsong at nmsu.edu> |
| License: |
LGPL (≥ 3) |
| NeedsCompilation: |
yes |
| Citation: |
GridOnClusters citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
GridOnClusters results |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=GridOnClusters
to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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