BayesCVI: Bayesian Cluster Validity Index

Algorithms for computing and generating plots with and without error bars for Bayesian cluster validity index (BCVI) (O. Preedasawakul, and N. Wiroonsri, A Bayesian Cluster Validity Index, Computational Statistics & Data Analysis, 202, 108053, 2025. <doi:10.1016/j.csda.2024.108053>) based on several underlying cluster validity indexes (CVIs) including Calinski-Harabasz, Chou-Su-Lai, Davies-Bouldin, Dunn, Pakhira-Bandyopadhyay-Maulik, Point biserial correlation, the score function, Starczewski, and Wiroonsri indices for hard clustering, and Correlation Cluster Validity, the generalized C, HF, KWON, KWON2, Modified Pakhira-Bandyopadhyay-Maulik, Pakhira-Bandyopadhyay-Maulik, Tang, Wiroonsri-Preedasawakul, Wu-Li, and Xie-Beni indices for soft clustering. The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage). Though BCVI is compatible with any underlying existing CVIs, we recommend users to use either WI or WP as the underlying CVI.

Version:	1.0.2
Depends:	R (≥ 2.10)
Imports:	e1071, mclust, ggplot2, UniversalCVI
Published:	2025-07-09
DOI:	10.32614/CRAN.package.BayesCVI
Author:	Nathakhun Wiroonsri [aut], Onthada Preedasawakul [cre, aut]
Maintainer:	Onthada Preedasawakul <o.preedasawakul at gmail.com>
License:	GPL (≥ 3)
NeedsCompilation:	no
Citation:	BayesCVI citation info
Materials:	README, NEWS
CRAN checks:	BayesCVI results

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