Package: SMMA 1.0.3

Adam Lund

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.

Authors:Adam Lund

SMMA_1.0.3.tar.gz
SMMA_1.0.3.tar.gz(r-4.5-noble)SMMA_1.0.3.tar.gz(r-4.4-noble)
SMMA_1.0.3.tgz(r-4.4-emscripten)SMMA_1.0.3.tgz(r-4.3-emscripten)
SMMA.pdf |SMMA.html
SMMA/json (API)

# Install 'SMMA' in R:
install.packages('SMMA', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

openblascpp

1.60 score 1 stars 4 scripts 133 downloads 4 mentions 2 exports 2 dependencies

Last updated 4 years agofrom:67649b6a82. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 16 2024
R-4.5-linux-x86_64NOTEDec 16 2024

Exports:RHsoftmaximin

Dependencies:RcppRcppArmadillo