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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 |
| 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 |
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