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) <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
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:	SMMA results

Documentation:

Reference manual:

SMMA.pdf

Downloads:

Package source:	SMMA_1.0.3.tar.gz
Windows binaries:	r-devel: SMMA_1.0.3.zip, r-release: SMMA_1.0.3.zip, r-oldrel: SMMA_1.0.3.zip
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

Linking:

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