RPMM: Recursively Partitioned Mixture Model

Recursively Partitioned Mixture Model for Beta and Gaussian Mixtures. This is a model-based clustering algorithm that returns a hierarchy of classes, similar to hierarchical clustering, but also similar to finite mixture models.

Version: 1.25
Depends: R (≥ 2.3.12), cluster
Published: 2017-02-28
DOI: 10.32614/CRAN.package.RPMM
Author: E. Andres Houseman, Sc.D. and Devin C. Koestler, Ph.D.
Maintainer: E. Andres Houseman <eahouseman at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
In views: Cluster, MachineLearning
CRAN checks: RPMM results


Reference manual: RPMM.pdf


Package source: RPMM_1.25.tar.gz
Windows binaries: r-devel: RPMM_1.25.zip, r-release: RPMM_1.25.zip, r-oldrel: RPMM_1.25.zip
macOS binaries: r-release (arm64): RPMM_1.25.tgz, r-oldrel (arm64): RPMM_1.25.tgz, r-release (x86_64): RPMM_1.25.tgz, r-oldrel (x86_64): RPMM_1.25.tgz
Old sources: RPMM archive

Reverse dependencies:

Reverse depends: ChAMP
Reverse imports: ENmix, EpiMix, MEAT, methylclock, MethylMix
Reverse suggests: RnBeads, sesame, wateRmelon


Please use the canonical form https://CRAN.R-project.org/package=RPMM to link to this page.