Clustering of Weighted Data
Build a clustrange object to compare different clustering solutions.
Convert a hierarchical clustering object to a seqtree object.
Cluster Quality Indices estimation by subsampling
Share of an association between an object (described by a dissimilarit...
Cluster quality statistics
Plot sequences according to a fuzzy clustering.
K-Medoids or PAM clustering of weighted data.
Compute wcKMedoids clustering for different number of clusters.
Plot of cluster quality of CLARA algorithm.
Robustness Assessment of Regressions using Cluster Analysis Typologies...
CLARA Clustering for Sequence Analysis
Automatic labeling of cluster using sequence medoids
Generate nonclustered sequence data according to different null models...
Sequence Analysis Typologies Validation Using Parametric Bootstrap
Monothetic clustering of state sequences
Aggregate identical cases.
Automatic comparison of clustering methods.
Compute the silhouette of each object using weighted data.
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).