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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 |
Reference manual: | rrMixture.pdf |
Vignettes: |
Introduction to rrMixture |
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 |
Please use the canonical form https://CRAN.R-project.org/package=rrMixture to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.