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


Reference manual: gofar.pdf


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


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