Package: RRRR 1.1.1

RRRR: Online Robust Reduced-Rank Regression Estimation

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>.

Authors:Yangzhuoran Fin Yang [aut, cre], Ziping Zhao [aut]

RRRR_1.1.1.tar.gz
RRRR_1.1.1.zip(r-4.7)RRRR_1.1.1.zip(r-4.6)RRRR_1.1.1.zip(r-4.5)
RRRR_1.1.1.tgz(r-4.6-any)RRRR_1.1.1.tgz(r-4.5-any)
RRRR_1.1.1.tar.gz(r-4.7-any)RRRR_1.1.1.tar.gz(r-4.6-any)
RRRR_1.1.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
RRRR/json (API)
NEWS

# Install 'RRRR' in R:
install.packages('RRRR', repos = c('https://finyang.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/finyang/rrrr/issues

Pkgdown/docs site:https://pkg.yangzhuoranyang.com

On CRAN:

Conda:

4.18 score 3 stars 10 scripts 214 downloads 4 exports 23 dependencies

Last updated from:f4353fcd29. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK104
source / vignettesOK197
linux-release-x86_64OK96
macos-release-arm64OK95
macos-oldrel-arm64OK79
windows-develOK90
windows-releaseOK65
windows-oldrelOK71
wasm-releaseOK99

Exports:ORRRRRRRRRR_simRRRR

Dependencies:clicpp11expmfarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMatrixmatrixcalcmvtnormR6RColorBrewerrlangS7scalesvctrsviridisLitewithr

Introduction to RRRR

Rendered fromRRRR.Rmdusingknitr::rmarkdownon May 13 2026.

Last update: 2023-02-24
Started: 2020-03-15