SMME: Soft Maximin Estimation for Large Scale Heterogeneous Data

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
Imports:	Rcpp (≥ 0.12.12)
LinkingTo:	Rcpp, RcppArmadillo
Published:	2022-05-01
Author:	Adam Lund [aut, cre]
Maintainer:	Adam Lund <adam.lund at math.ku.dk>
License:	MIT + file LICENSE
NeedsCompilation:	yes
CRAN checks:	SMME results

Documentation:

Reference manual:

SMME.pdf

Downloads:

Package source:	SMME_1.1.tar.gz
Windows binaries:	r-devel: SMME_1.1.zip, r-release: SMME_1.1.zip, r-oldrel: SMME_1.1.zip
macOS binaries:	r-release (arm64): SMME_1.1.tgz, r-oldrel (arm64): SMME_1.1.tgz, r-release (x86_64): SMME_1.1.tgz, r-oldrel (x86_64): SMME_1.1.tgz
Old sources:	SMME archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=SMME to link to this page.