vimixr: Collapsed Variational Inference for Dirichlet Process (DP)
Mixture Model
Collapsed Variational Inference for a Dirichlet Process (DP) mixture model with unknown covariance matrix structure and DP concentration parameter. It enables efficient clustering of high-dimensional data with significantly improved computational speed than traditional MCMC methods. The package incorporates 8 parameterisations and corresponding prior choices for the unknown covariance matrix, from which the user can choose and apply accordingly.
| Version: |
0.1.2 |
| Imports: |
ggplot2, patchwork, Rcpp, Rfast, rlang, parallel, stats |
| LinkingTo: |
Rcpp, RcppEigen |
| Suggests: |
knitr, rmarkdown, pbapply, testthat (≥ 3.0.0) |
| Published: |
2026-01-12 |
| DOI: |
10.32614/CRAN.package.vimixr (may not be active yet) |
| Author: |
Annesh Pal  [aut,
cre],
Boris Hejblum
[aut] |
| Maintainer: |
Annesh Pal <sistm.soft.maintain at gmail.com> |
| BugReports: |
https://github.com/annesh07/vimixr/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/annesh07/vimixr |
| NeedsCompilation: |
yes |
| Materials: |
README, NEWS |
| CRAN checks: |
vimixr results |
Documentation:
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