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). Joint grid discretization
is applicable as a data transformation step to prepare data for
model-free inference of association, function, or causality.
| Version: |
0.0.8 |
| Depends: |
R (≥ 3.0) |
| Imports: |
Rcpp, cluster, fossil, dqrng, Rdpack, plotrix |
| LinkingTo: |
Rcpp |
| Suggests: |
Ckmeans.1d.dp, FunChisq, knitr, testthat (≥ 2.1.0), rmarkdown |
| Published: |
2020-09-15 |
| 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 |
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