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
DOI:	10.32614/CRAN.package.VALIDICLUST
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, r-oldrel (x86_64): VALIDICLUST_0.1.0.tgz

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