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BNPMIXcluster (version 1.1.0)

Bayesian Nonparametric Model for Clustering with Mixed Scale Variables

Description

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) .

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Version

Install

install.packages('BNPMIXcluster')

Monthly Downloads

25

Version

1.1.0

License

GPL (>= 2)

Maintainer

Christian Carmona

Last Published

August 31st, 2017

Functions in BNPMIXcluster (1.1.0)

sampling_Omega_ij

Simulation of "\(\Omega_{i,j}\)" in the mixdpcluster model for bayesian clustering.
sampling_a

Simulation of "\(a\)" in the mixdpcluster model for bayesian clustering.
plot.MIXcluster

Plotting clustering results for "MIXcluster" objects
poverty.data

Poverty data for testing the BNPMIXcluster package
MIXclustering

Bayesian Nonparametric Model for Clustering with Mixed Scale Variables
get_latents

Simulation of latent variables \(Z\) in the mixdpclust model
sim.cluster.data

Simulated data for testing the BNPMIXcluster package
summary.MIXcluster

Summarizing clustering results