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VALIDICLUST  

VALID Inference for Clusters Separation Testing
View on CRAN: Click here


Download and install VALIDICLUST package within the R console
Install from CRAN:
install.packages("VALIDICLUST")

Install from Github:
library("remotes")
install_github("cran/VALIDICLUST")

Install by package version:
library("remotes")
install_version("VALIDICLUST", "0.1.0")



Attach the package and use:
library("VALIDICLUST")
Maintained by
Benjamin Hivert
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-12-01
Latest Update: 2022-12-01
Description:
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>.
How to cite:
Benjamin Hivert (2022). VALIDICLUST: VALID Inference for Clusters Separation Testing. R package version 0.1.0, https://cran.r-project.org/web/packages/VALIDICLUST. Accessed 21 Nov. 2024.
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Complete documentation for VALIDICLUST
Functions, R codes and Examples using the VALIDICLUST R package
Some associated functions: merge_selective_inference . test_multimod . test_selective_inference . 
Some associated R codes: merge_selective_inference.R . multimod.R . selective_inference.R . utils.R .  Full VALIDICLUST package functions and examples
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