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:
RRRR_1.1.1.tar.gz
RRRR_1.1.1.zip(r-4.5)RRRR_1.1.1.zip(r-4.4)RRRR_1.1.1.zip(r-4.3)
RRRR_1.1.1.tgz(r-4.4-any)RRRR_1.1.1.tgz(r-4.3-any)
RRRR_1.1.1.tar.gz(r-4.5-noble)RRRR_1.1.1.tar.gz(r-4.4-noble)
RRRR_1.1.1.tgz(r-4.4-emscripten)RRRR_1.1.1.tgz(r-4.3-emscripten)
RRRR.pdf |RRRR.html✨
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
Last updated 2 years agofrom:f4353fcd29. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 16 2024 |
| R-4.5-win | OK | Nov 16 2024 |
| R-4.5-linux | OK | Nov 16 2024 |
| R-4.4-win | OK | Nov 16 2024 |
| R-4.4-mac | OK | Nov 16 2024 |
| R-4.3-win | OK | Nov 16 2024 |
| R-4.3-mac | OK | Nov 16 2024 |
Dependencies:clicolorspaceexpmfansifarverggplot2gluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmatrixcalcmgcvmunsellmvtnormnlmepillarpkgconfigR6RColorBrewerrlangscalestibbleutf8vctrsviridisLitewithr
