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>.

Getting started

Package details

AuthorChristian Carmona [aut, cre], Luis Nieto-Barajas [aut], Antonio Canale [ctb]
MaintainerChristian Carmona <[email protected]>
LicenseGPL (>= 2)
Version1.2.4
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("BNPMIXcluster")

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BNPMIXcluster documentation built on Sept. 27, 2017, 1:02 a.m.