Bayesian Nonparametric Model for Clustering with Mixed Scale Variables

Model-based approach for clustering of multivariate data, capable of combining different types of variables (continuous, ordinal and nominal) and accommodating 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. Details of the underlying model is described in Carmona, C., Nieto-Barajas, L. E., Canale, A. (2016) .


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install.packages("BNPMIXcluster")

1.3 by Christian Carmona, 10 months ago


https://github.com/christianu7/BNPMIXcluster


Report a bug at https://github.com/christianu7/BNPMIXcluster/issues


Browse source code at https://github.com/cran/BNPMIXcluster


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


Documentation:   PDF Manual  


MIT + file LICENSE license


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

Suggests scatterplot3d

Linking to Rcpp, RcppArmadillo


See at CRAN