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:

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