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 (2021) <arXiv:1805.02407>. Currently Lasso and SCAD penalized estimation is implemented. Note this package subsumes and replaces the SMMA package.

Version: 1.0.1
Imports: Rcpp (≥ 0.12.12)
LinkingTo: Rcpp, RcppArmadillo
Published: 2021-07-22
Author: Adam Lund
Maintainer: Adam Lund <adam.lund at math.ku.dk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: SMME results

Documentation:

Reference manual: SMME.pdf

Downloads:

Package source: SMME_1.0.1.tar.gz
Windows binaries: r-devel: SMME_1.0.1.zip, r-devel-UCRT: SMME_1.0.1.zip, r-release: SMME_1.0.1.zip, r-oldrel: SMME_1.0.1.zip
macOS binaries: r-release (arm64): SMME_1.0.1.tgz, r-release (x86_64): SMME_1.0.1.tgz, r-oldrel: SMME_1.0.1.tgz
Old sources: SMME archive

Linking:

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