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BNPMIXcluster: 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) <arXiv:1612.00083>.
Getting started
Browse package contents
Package details |
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| Author | Christian Carmona [aut, cre] (<https://orcid.org/0000-0003-0224-4968>), Luis Nieto-Barajas [aut] (<https://orcid.org/0000-0002-0859-7679>), Antonio Canale [ctb] (<https://orcid.org/0000-0002-5403-0040>) |
| Maintainer | Christian Carmona <carmona@stats.ox.ac.uk> |
| License | MIT + file LICENSE |
| Version | 1.3 |
| URL | https://github.com/christianu7/BNPMIXcluster |
| Package repository | View on CRAN |
| Installation |
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