rrMixture: Reduced-Rank Mixture Models

We implement full-ranked, rank-penalized, and adaptive nuclear norm penalized estimation methods using multivariate mixture models proposed by Kang, Chen, and Yao (2022+).

Version: 0.1-1
Depends: R (≥ 3.4.0)
Imports: MASS, Rcpp (≥ 1.0.7), Matrix, matrixcalc, gtools, utils
LinkingTo: Rcpp, RcppArmadillo
Suggests: bayesm, rrpack, knitr, rmarkdown
Published: 2022-03-10
Author: Suyeon Kang [aut, cre], Weixin Yao [aut], Kun Chen [aut]
Maintainer: Suyeon Kang <skang062 at ucr.edu>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: rrMixture results

Documentation:

Reference manual: rrMixture.pdf
Vignettes: Introduction to rrMixture

Downloads:

Package source: rrMixture_0.1-1.tar.gz
Windows binaries: r-devel: rrMixture_0.1-1.zip, r-release: rrMixture_0.1-1.zip, r-oldrel: rrMixture_0.1-1.zip
macOS binaries: r-release (arm64): rrMixture_0.1-1.tgz, r-release (x86_64): rrMixture_0.1-1.tgz, r-oldrel: rrMixture_0.1-1.tgz

Linking:

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