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) .


Reference manual

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1.2.4 by Christian Carmona, a year ago

Browse source code at

Authors: Christian Carmona [aut, cre] , Luis Nieto-Barajas [aut] , Antonio Canale [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp, truncnorm

Suggests scatterplot3d

Linking to Rcpp, RcppArmadillo

See at CRAN