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gofar: Generalized Co-Sparse Factor Regression

Divide and conquer approach for estimating low-rank and sparse coefficient matrix in the generalized co-sparse factor regression. Please refer the manuscript 'Mishra, Aditya, Dipak K. Dey, Yong Chen, and Kun Chen. Generalized co-sparse factor regression. Computational Statistics & Data Analysis 157 (2021): 107127' for more details.

Version:0.1
Depends:R (≥ 3.5), stats, utils
Imports:Rcpp (≥ 0.12.9),MASS,magrittr,rrpack,glmnet
LinkingTo:Rcpp,RcppArmadillo
Published:2022-03-02
DOI:10.32614/CRAN.package.gofar
Author:Aditya Mishra [aut, cre], Kun Chen [aut]
Maintainer:Aditya Mishra <amishra at flatironinstitute.org>
License:GPL (≥ 3.0)
URL:https://github.com/amishra-stats/gofar,https://www.sciencedirect.com/science/article/pii/S0167947320302188
NeedsCompilation:yes
Language:en-US
CRAN checks:gofar results

Documentation:

Reference manual:gofar.html ,gofar.pdf

Downloads:

Package source: gofar_0.1.tar.gz
Windows binaries: r-devel:gofar_0.1.zip, r-release:gofar_0.1.zip, r-oldrel:gofar_0.1.zip
macOS binaries: r-release (arm64):gofar_0.1.tgz, r-oldrel (arm64):gofar_0.1.tgz, r-release (x86_64):gofar_0.1.tgz, r-oldrel (x86_64):gofar_0.1.tgz

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=gofarto link to this page.


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