pfclust: Power Fuzzy Clustering and Cluster-Wise Regression

Implementations of Power Fuzzy Clustering (PFC) and Power Fuzzy Cluster-wise Regression (PFCR) for multivariate data. The package supports Minkowski distances, with the L1 case solved via iteratively re-weighted least squares and the case p > 1 solved via coordinate-wise root finding, as well as an adaptive, regularised Mahalanobis distance with per-cluster covariance matrices. Both plain fuzzy clustering and cluster-wise linear regression are provided. The corresponding paper can be found at Nguyen P.T., Tortora C., and Punzo A. (2026) <doi:10.1109/TFUZZ.2026.3683998>.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: stats
Suggests: flexCWM
Published: 2026-04-28
DOI: 10.32614/CRAN.package.pfclust
Author: Phuc Thinh Nguyen [aut, cre], Cristina Tortora [aut, ths, dgs], Antonio Punzo [aut, ths, dgs]
Maintainer: Phuc Thinh Nguyen <phucthinh010603 at yahoo.com>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README
CRAN checks: pfclust results

Documentation:

Reference manual: pfclust.html , pfclust.pdf

Downloads:

Package source: pfclust_0.1.0.tar.gz
Windows binaries: r-devel: pfclust_0.1.0.zip, r-release: pfclust_0.1.0.zip, r-oldrel: pfclust_0.1.0.zip
macOS binaries: r-release (arm64): pfclust_0.1.0.tgz, r-oldrel (arm64): pfclust_0.1.0.tgz, r-release (x86_64): not available, r-oldrel (x86_64): not available

Linking:

Please use the canonical form https://CRAN.R-project.org/package=pfclust to link to this page.