Clusters state sequences and weighted data. It provides an optimized weighted PAM algorithm as well as functions for aggregating replicated cases, computing cluster quality measures for a range of clustering solutions, sequence analysis typology validation using parametric bootstraps and plotting (fuzzy) clusters of state sequences. It further provides a fuzzy and crisp CLARA algorithm to cluster large database with sequence analysis, and a methodological framework for Robustness Assessment of Regressions using Cluster Analysis Typologies (RARCAT).
| Version: |
2.0 |
| Depends: |
R (≥ 3.0.0), TraMineR (≥ 2.0-6), cluster |
| Imports: |
utils, RColorBrewer, foreach, progressr, future, doFuture, nnet, fastcluster, vegclust, lme4, margins |
| Suggests: |
RUnit, knitr, isotone, vegan, lattice, rmarkdown, Cairo, progress, DirichletReg, betareg, fpc |
| Published: |
2025-12-10 |
| DOI: |
10.32614/CRAN.package.WeightedCluster |
| Author: |
Matthias Studer [aut, cre],
Leonard Roth [ctb] |
| Maintainer: |
Matthias Studer <matthias.studer at unige.ch> |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
http://mephisto.unige.ch/weightedcluster/ |
| NeedsCompilation: |
yes |
| Citation: |
WeightedCluster citation info |
| Materials: |
NEWS |
| CRAN checks: |
WeightedCluster results |