Distance-Based k-Medoids R package kmed version 0.4.2 Algorithms of distance-based k-medoids clustering: simple and fast k-medoids, ranked k-medoids, and increasing number of clusters in k-medoids. Calculate distances for mixed variable data such as Gower, Podani, Wishart, Huang, Harikumar-PV, and Ahmad-Dey. Cluster validation applies internal and relative criteria. The internal criteria includes silhouette index and shadow values. The relative criterium applies bootstrap procedure producing a heatmap with a flexible reordering matrix algorithm such as complete, ward, or average linkages. The cluster result can be plotted in a marked barplot or pca biplot. Software Depends: R (>= 2.10) Imports: ggplot2 Suggests: knitr, rmarkdown Weksi Budiaji <budiaji@untirta.ac.id> Comprehensive R Archive Network (CRAN) Weksi Budiaji [aut, cre] GPL-3 2022-08-29 application/tgz https://CRAN.R-project.org/package=kmed doi:10.32614/CRAN.package.kmed