The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
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[@]dogado.de.
An implementation of both the equality and inequality constrained lasso functions for the algorithm described in "Penalized and Constrained Optimization" by James, Paulson, and Rusmevichientong (Journal of the American Statistical Association, 2019; see <http://www-bcf.usc.edu/~gareth/research/PAC.pdf> for a full-text version of the paper). The algorithm here is designed to allow users to define linear constraints (either equality or inequality constraints) and use a penalized regression approach to solve the constrained problem. The functions here are used specifically for constraints with the lasso formulation, but the method described in the PaC paper can be used for a variety of scenarios. In addition to the simple examples included here with the corresponding functions, complete code to entirely reproduce the results of the paper is available online through the Journal of the American Statistical Association.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.3.0), methods (≥ 3.4.4), penalized (≥ 0.9) |
| Imports: | MASS (≥ 7.3), lars (≥ 1.2), quadprog (≥ 1.5), limSolve (≥ 1.5.5.3) |
| Published: | 2019-04-29 |
| Author: | Courtney Paulson [aut, cre], Gareth James [ctb], Paat Rusmevichientong [ctb] |
| Maintainer: | Courtney Paulson <cpaulson at rhsmith.umd.edu> |
| License: | GPL-3 |
| URL: | http://www-bcf.usc.edu/~gareth/research/PAC.pdf |
| NeedsCompilation: | no |
| CRAN checks: | PACLasso results |
| Reference manual: | PACLasso.pdf |
| Package source: | PACLasso_1.0.0.tar.gz |
| Windows binaries: | r-devel: PACLasso_1.0.0.zip, r-release: PACLasso_1.0.0.zip, r-oldrel: PACLasso_1.0.0.zip |
| macOS binaries: | r-release (arm64): PACLasso_1.0.0.tgz, r-oldrel (arm64): PACLasso_1.0.0.tgz, r-release (x86_64): PACLasso_1.0.0.tgz, r-oldrel (x86_64): PACLasso_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=PACLasso 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.
Health stats visible at Monitor.