_            _    _        _         _
      /\ \         /\ \ /\ \     /\_\      / /\
      \_\ \       /  \ \\ \ \   / / /     / /  \
      /\__ \     / /\ \ \\ \ \_/ / /     / / /\ \__
     / /_ \ \   / / /\ \ \\ \___/ /     / / /\ \___\
    / / /\ \ \ / / /  \ \_\\ \ \_/      \ \ \ \/___/
   / / /  \/_// / /   / / / \ \ \        \ \ \
  / / /      / / /   / / /   \ \ \   _    \ \ \
 / / /      / / /___/ / /     \ \ \ /_/\__/ / /
/_/ /      / / /____\/ /       \ \_\\ \/___/ /
\_\/       \/_________/         \/_/ \_____\/
r-weightedcluster 2.0
Propagated dependencies: r-vegclust@2.0.3 r-traminer@2.2-13 r-rcolorbrewer@1.1-3 r-progressr@0.18.0 r-nnet@7.3-20 r-margins@0.3.28 r-lme4@1.1-37 r-future@1.68.0 r-foreach@1.5.2 r-fastcluster@1.3.0 r-dofuture@1.1.2 r-cluster@2.1.8.1
Channel: guix-cran
Location: guix-cran/packages/w.scm (guix-cran packages w)
Home page: http://mephisto.unige.ch/weightedcluster/
Licenses: GPL 2+
Synopsis: Clustering of Weighted Data
Description:

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).

Total results: 1