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.
Efficient procedure for solving the soft maximin problem for large scale heterogeneous data, see Lund, Mogensen and Hansen (2022) <doi:10.1111/sjos.12580>. Currently Lasso and SCAD penalized estimation is implemented. Note this package subsumes and replaces the SMMA package.
Version: | 1.1.1 |
Imports: | Rcpp (≥ 0.12.12) |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2023-01-08 |
DOI: | 10.32614/CRAN.package.SMME |
Author: | Adam Lund [aut, cre] |
Maintainer: | Adam Lund <adam.lund at math.ku.dk> |
License: | MIT + file LICENSE |
NeedsCompilation: | yes |
CRAN checks: | SMME results |
Reference manual: | SMME.pdf |
Package source: | SMME_1.1.1.tar.gz |
Windows binaries: | r-devel: SMME_1.1.1.zip, r-release: SMME_1.1.1.zip, r-oldrel: SMME_1.1.1.zip |
macOS binaries: | r-release (arm64): SMME_1.1.1.tgz, r-oldrel (arm64): SMME_1.1.1.tgz, r-release (x86_64): SMME_1.1.1.tgz, r-oldrel (x86_64): SMME_1.1.1.tgz |
Old sources: | SMME archive |
Please use the canonical form https://CRAN.R-project.org/package=SMME 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.