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GridOnClusters: Cluster-Preserving Multivariate Joint Grid Discretization
Discretize multivariate continuous data using a grid
that captures the joint distribution via preserving clusters in
the original data (Wang et al. 2020) <doi:10.1145/3388440.3412415>.
Joint grid discretization is applicable as a data transformation step
to prepare data for model-free inference of association, function, or
causality.
| Version: |
0.1.0.1 |
| Imports: |
Rcpp, Ckmeans.1d.dp, cluster, fossil, dqrng, mclust, Rdpack, plotrix |
| LinkingTo: |
Rcpp |
| Suggests: |
FunChisq, knitr, testthat (≥ 3.0.0), rmarkdown |
| Published: |
2024-05-10 |
| Author: |
Jiandong Wang [aut],
Sajal Kumar  [aut],
Joe Song [aut,
cre] |
| Maintainer: |
Joe Song <joemsong at cs.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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