Package: rrMixture 0.1-2
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+).
Authors:
rrMixture_0.1-2.tar.gz
rrMixture_0.1-2.zip(r-4.7-x86_64)rrMixture_0.1-2.zip(r-4.7-arm64)rrMixture_0.1-2.zip(r-4.6-x86_64)rrMixture_0.1-2.zip(r-4.6-arm64)
rrMixture_0.1-2.tar.gz(r-4.7-arm64)rrMixture_0.1-2.tar.gz(r-4.7-x86_64)rrMixture_0.1-2.tar.gz(r-4.6-arm64)rrMixture_0.1-2.tar.gz(r-4.6-x86_64)
rrMixture_0.1-2.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
rrMixture/json (API)
| # Install 'rrMixture' in R: |
| install.packages('rrMixture', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated from:6c87645d9b. Checks:10 OK. Indexed: no.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 97 | ||
| linux-devel-x86_64 | OK | 128 | ||
| source / vignettes | OK | 607 | ||
| linux-release-arm64 | OK | 118 | ||
| linux-release-x86_64 | OK | 121 | ||
| windows-devel-arm64 | OK | 294 | ||
| windows-devel-x86_64 | OK | 144 | ||
| windows-release-arm64 | OK | 226 | ||
| windows-release-x86_64 | OK | 103 | ||
| wasm-release | OK | 105 |
Exports:initialize.pararrmixrrmix.sim.normtune.rrmix
Dependencies:gtoolslatticeMASSMatrixmatrixcalcRcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Initialization of Parameter Estimates | initialize.para |
| Visualize rrmix Objects | plot plot.rrmix plot.tune.rrmix |
| Reduced-Rank Mixture Models in Multivariate Regression | rrmix |
| Simulation Data Generator | rrmix.sim.norm |
| rrMixture: Reduced-Rank Mixture Models. | rrMixture |
| Summarize rrmix Objects | summary summary.rrmix summary.tune.rrmix |
| Reduced-rank mixture models with optimal tuning parameter(s) | tune.rrmix |
