The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
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 |
Please use the canonical form https://CRAN.R-project.org/package=gofar to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.