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>.
| Version: |
1.3 |
| Depends: |
R (≥ 2.10) |
| Imports: |
compiler, gplots, MASS, matrixcalc, mvtnorm, plyr, Rcpp (≥
1.0.5), truncnorm |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
scatterplot3d |
| Published: |
2020-11-30 |
| Author: |
Christian Carmona 
[aut, cre],
Luis Nieto-Barajas
[aut],
Antonio Canale
[ctb] |
| Maintainer: |
Christian Carmona <carmona at stats.ox.ac.uk> |
| BugReports: |
https://github.com/christianu7/BNPMIXcluster/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/christianu7/BNPMIXcluster |
| NeedsCompilation: |
yes |
| Materials: |
README NEWS |
| CRAN checks: |
BNPMIXcluster results |
Documentation:
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