Package: MergeKmeans 0.3.0

MergeKmeans: Clustering Large Datasets by Merging K-Means Solutions

Fast clustering of large datasets by hierarchically merging components of a K-means solution based on the pairwise overlap between the Gaussian mixture components implied by the K-means partition, as proposed by Melnykov and Michael (2020) <doi:10.1007/s00357-019-09314-8>. Implements the DEMP-K merging algorithm with single, Ward's, average, and complete linkages, the overlap map display for selecting the number of clusters, four K-means variants corresponding to Gaussian mixtures with spherical or elliptical, homoscedastic or heteroscedastic components, and a tool for selecting the number of K-means components.

Authors:Aqi Dong [aut, cre], Volodymyr Melnykov [aut], Yang-Li Liao [aut], Peng Li [aut], Xuejian Li [aut]