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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 math.ku.dk> |
| 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: 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 |
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These binaries (installable software) and packages are in development.
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