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Methods for estimating online robust reduced-rank regression. The Gaussian maximum likelihood estimation method is described in Johansen, S. (1991) <doi:10.2307/2938278>. The majorisation-minimisation estimation method is partly described in Zhao, Z., & Palomar, D. P. (2017) <doi:10.1109/GlobalSIP.2017.8309093>. The description of the generic stochastic successive upper-bound minimisation method and the sample average approximation can be found in Razaviyayn, M., Sanjabi, M., & Luo, Z. Q. (2016) <doi:10.1007/s10107-016-1021-7>.
Version: | 1.1.1 |
Imports: | matrixcalc, expm, ggplot2, magrittr, mvtnorm, stats |
Suggests: | lazybar, knitr, rmarkdown |
Published: | 2023-02-24 |
DOI: | 10.32614/CRAN.package.RRRR |
Author: | Yangzhuoran Fin Yang
|
Maintainer: | Yangzhuoran Fin Yang <yangyangzhuoran at gmail.com> |
BugReports: | https://github.com/FinYang/RRRR/issues/ |
License: | GPL-3 |
URL: | https://pkg.yangzhuoranyang.com/RRRR/, https://github.com/FinYang/RRRR |
NeedsCompilation: | no |
Language: | en-AU |
Materials: | README NEWS |
CRAN checks: | RRRR results |
Reference manual: | RRRR.pdf |
Vignettes: |
Introduction to RRRR |
Package source: | RRRR_1.1.1.tar.gz |
Windows binaries: | r-devel: RRRR_1.1.1.zip, r-release: RRRR_1.1.1.zip, r-oldrel: RRRR_1.1.1.zip |
macOS binaries: | r-release (arm64): RRRR_1.1.1.tgz, r-oldrel (arm64): RRRR_1.1.1.tgz, r-release (x86_64): RRRR_1.1.1.tgz, r-oldrel (x86_64): RRRR_1.1.1.tgz |
Old sources: | RRRR archive |
Please use the canonical form https://CRAN.R-project.org/package=RRRR 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.
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