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>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: BNPMIXcluster results


Reference manual: BNPMIXcluster.pdf
Package source: BNPMIXcluster_1.2.4.tar.gz
Windows binaries: r-devel:, r-devel-gcc8:, r-release:, r-oldrel:
OS X binaries: r-release: BNPMIXcluster_1.2.4.tgz, r-oldrel: BNPMIXcluster_1.2.4.tgz
Old sources: BNPMIXcluster archive


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