BNPMIXcluster: Bayesian Nonparametric Model for Clustering with Mixed Scale Variables

Bayesian nonparametric approach for clustering that is capable to combine different types of variables (continuous, ordinal and nominal) and also accommodates for different sampling probabilities in a complex survey design. The model is based on a location mixture model with a Poisson-Dirichlet process prior on the location parameters of the associated latent variables. The package performs the clustering model described in Carmona, C., Nieto-Barajas, L. E., Canale, A. (2016) <arXiv:1612.00083>.

Version: 1.2.4
Depends: R (≥ 2.10)
Imports: compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp, truncnorm
LinkingTo: Rcpp, RcppArmadillo
Suggests: scatterplot3d
Published: 2017-09-26
Author: Christian Carmona [aut, cre], Luis Nieto-Barajas [aut], Antonio Canale [ctb]
Maintainer: Christian Carmona <carmona at stats.ox.ac.uk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: BNPMIXcluster results

Downloads:

Reference manual: BNPMIXcluster.pdf
Package source: BNPMIXcluster_1.2.4.tar.gz
Windows binaries: r-devel: BNPMIXcluster_1.2.4.zip, r-release: BNPMIXcluster_1.2.4.zip, r-oldrel: BNPMIXcluster_1.2.4.zip
OS X El Capitan binaries: r-release: BNPMIXcluster_1.2.4.tgz
OS X Mavericks binaries: r-oldrel: BNPMIXcluster_1.2.4.tgz
Old sources: BNPMIXcluster archive

Linking:

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