SMMA: Soft Maximin Estimation for Large Scale Array-Tensor Models

Efficient design matrix free procedure for solving a soft maximin problem for large scale array-tensor structured models, see Lund, Mogensen and Hansen (2019) <doi:10.48550/arXiv.1805.02407>. Currently Lasso and SCAD penalized estimation is implemented.

Version: 1.0.3
Imports: Rcpp (≥ 0.12.12)
LinkingTo: Rcpp, RcppArmadillo
Published: 2020-09-17
DOI: 10.32614/CRAN.package.SMMA
Author: Adam Lund
Maintainer: Adam Lund <adam.lund at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
CRAN checks: SMMA results


Reference manual: SMMA.pdf


Package source: SMMA_1.0.3.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): SMMA_1.0.3.tgz, r-oldrel (arm64): SMMA_1.0.3.tgz, r-release (x86_64): SMMA_1.0.3.tgz, r-oldrel (x86_64): SMMA_1.0.3.tgz
Old sources: SMMA archive


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