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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:0.1-2
Depends:R (≥ 3.4.0)
Imports:MASS,Rcpp (≥ 1.0.8),Matrix,matrixcalc,gtools, utils
LinkingTo:Rcpp,RcppArmadillo
Suggests:bayesm,rrpack,knitr,rmarkdown
Published:2022-04-08
DOI:10.32614/CRAN.package.rrMixture
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.html ,rrMixture.pdf
Vignettes:Introduction to rrMixture (source,R code)

Downloads:

Package source: rrMixture_0.1-2.tar.gz
Windows binaries: r-devel:rrMixture_0.1-2.zip, r-release:rrMixture_0.1-2.zip, r-oldrel:rrMixture_0.1-2.zip
macOS binaries: r-release (arm64):rrMixture_0.1-2.tgz, r-oldrel (arm64):rrMixture_0.1-2.tgz, r-release (x86_64):rrMixture_0.1-2.tgz, r-oldrel (x86_64):rrMixture_0.1-2.tgz
Old sources: rrMixture archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=rrMixtureto link to this page.


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