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RRRR  

Online Robust Reduced-Rank Regression Estimation
View on CRAN: Click here


Download and install RRRR package within the R console
Install from CRAN:
install.packages("RRRR")

Install from Github:
library("remotes")
install_github("cran/RRRR")

Install by package version:
library("remotes")
install_version("RRRR", "1.1.1")



Attach the package and use:
library("RRRR")
Maintained by
Yangzhuoran Fin Yang
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-20
Latest Update: 2023-02-24
Description:
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>.
How to cite:
Yangzhuoran Fin Yang (2020). RRRR: Online Robust Reduced-Rank Regression Estimation. R package version 1.1.1, https://cran.r-project.org/web/packages/RRRR
Previous versions and publish date:
1.0.0 (2020-03-20 16:10), 1.1.0 (2020-05-08 15:10)
Other packages that cited RRRR R package
View RRRR citation profile
Other R packages that RRRR depends, imports, suggests or enhances
Functions, R codes and Examples using the RRRR R package
Some associated functions: ORRRR . RRR . RRRR-package . RRRR . RRR_sim . plot.RRRR . update.RRRR . 
Some associated R codes: ORRRR.R . ORRRR_class.R . RRR.R . RRRR-package.R . RRRR.R . RRRR_class.R . RRR_class.R . simulation.R . update.R .  Full RRRR package functions and examples
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