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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 |
| Reference manual: | VALIDICLUST.pdf |
| 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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