VALIDICLUST: VALID Inference for Clusters Separation Testing

Given a partition resulting from any clustering algorithm, the implemented tests allow valid post-clustering inference by testing if a given variable significantly separates two of the estimated clusters. Methods are detailed in: Hivert B, Agniel D, Thiebaut R & Hejblum BP (2022). "Post-clustering difference testing: valid inference and practical considerations", <doi:10.48550/arXiv.2210.13172>.

Version: 0.1.0
Depends: R (≥ 3.6)
Imports: diptest, dplyr
Published: 2022-12-01
Author: Benjamin Hivert
Maintainer: Benjamin Hivert <benjamin.hivert at u-bordeaux.fr>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: VALIDICLUST results

Documentation:

Reference manual: VALIDICLUST.pdf

Downloads:

Package source: VALIDICLUST_0.1.0.tar.gz
Windows binaries: r-devel: VALIDICLUST_0.1.0.zip, r-release: VALIDICLUST_0.1.0.zip, r-oldrel: VALIDICLUST_0.1.0.zip
macOS binaries: r-release (arm64): VALIDICLUST_0.1.0.tgz, r-oldrel (arm64): VALIDICLUST_0.1.0.tgz, r-release (x86_64): VALIDICLUST_0.1.0.tgz

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