[aut, cre],
Ziping Zhao [aut]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: | 1.1.0 |
| Imports: | matrixcalc, expm, ggplot2, magrittr, mvtnorm, stats |
| Suggests: | lazybar, knitr, rmarkdown |
| Published: | 2020-05-08 |
| Author: | Yangzhuoran Yang
[aut, cre],
Ziping Zhao [aut] |
| Maintainer: | Yangzhuoran Yang <Fin.Yang at monash.edu> |
| 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_1.1.0.tar.gz |
| Windows binaries: | r-devel: RRRR_1.1.0.zip, r-release: RRRR_1.1.0.zip, r-oldrel: RRRR_1.1.0.zip |
| macOS binaries: | r-release: RRRR_1.1.0.tgz, r-oldrel: RRRR_1.1.0.tgz |
| Old sources: | RRRR archive |
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