Collapsed Variational Inference for Dirichlet Process (DP) Mixture Model R package vimixr version 0.1.2 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. Software Imports: ggplot2, patchwork, Rcpp, Rfast, rlang, parallel, stats LinkingTo: Rcpp, RcppEigen Suggests: knitr, rmarkdown, pbapply, testthat (>= 3.0.0) Annesh Pal <sistm.soft.maintain@gmail.com> Comprehensive R Archive Network (CRAN) Annesh Pal [aut, cre] (ORCID: <https://orcid.org/0009-0003-2146-180X>), Boris Hejblum [aut] (ORCID: <https://orcid.org/0000-0003-0646-452X>) MIT + file LICENSE (https://CRAN.R-project.org/package=vimixr/LICENSE) 2026-01-12 application/tgz https://CRAN.R-project.org/package=vimixr doi:10.32614/CRAN.package.vimixr