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>
License: MIT + file LICENSE
NeedsCompilation: yes
CRAN checks: SMME results


Reference manual: SMME.pdf


Package source: SMME_1.1.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
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


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