Package: SMME 1.1.1
Adam Lund
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 (2022) <doi:10.1111/sjos.12580>. Currently Lasso and SCAD penalized estimation is implemented. Note this package subsumes and replaces the SMMA package.
Authors:
SMME_1.1.1.tar.gz
SMME_1.1.1.tar.gz(r-4.5-noble)SMME_1.1.1.tar.gz(r-4.4-noble)
SMME_1.1.1.tgz(r-4.4-emscripten)SMME_1.1.1.tgz(r-4.3-emscripten)
SMME.pdf |SMME.html✨
SMME/json (API)
| # Install 'SMME' in R: |
| install.packages('SMME', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
Uses libs:
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:2d6fd72cd3. Checks:OK: 1 NOTE: 1. Indexed: no.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 21 2024 |
| R-4.5-linux-x86_64 | NOTE | Oct 21 2024 |
Exports:iwtpredict.SMMERHsoftmaximinwt
Dependencies:RcppRcppArmadillo
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Inverse discrete wavelet transform | iwt |
| Make Prediction From a SMME Object | predict.SMME SMME.predict SMME_predict |
| Print Function for objects of Class SMME | print.SMME |
| The Rotated H-transform of a 3d Array by a Matrix | H RH Rotate SMME_RH |
| Soft Maximin Estimation for Large Scale Heterogenous Data | pga SMME softmaximin |
| Discrete wavelet transform | wt |
