Clustering Large Datasets by Merging K-Means Solutions R package MergeKmeans version 0.2.0 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. Software Imports: stats, graphics, grDevices, utils, parallel Suggests: CompQuadForm, MixSim, mclust, broom, tibble, testthat (>= 3.0.0), knitr, rmarkdown Aqi Dong <donga2@erau.edu> Comprehensive R Archive Network (CRAN) Aqi Dong [aut, cre] (ORCID: <https://orcid.org/0009-0004-1676-3528>), Volodymyr Melnykov [aut], Yang-Li Liao [aut], Peng Li [aut], Xuejian Li [aut] GPL (>= 2) 2026-07-19 application/tgz https://CRAN.R-project.org/package=MergeKmeans doi:10.32614/CRAN.package.MergeKmeans