A flexible framework combining
variable screening and random projection techniques for fitting ensembles of
predictive generalized linear models to high-dimensional data.
Designed for extensibility, the package implements
key techniques as S3 classes with user-friendly constructors,
enabling easy integration and development of new procedures for
high-dimensional applications. For more details see
Parzer et al (2024a) <doi:10.48550/arXiv.2312.00130> and
Parzer et al (2024b) <doi:10.48550/arXiv.2410.00971>.
| Version: |
1.1.1 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
Matrix, ROCR, Rdpack, ggplot2, rlang, glmnet, methods |
| Suggests: |
testthat (≥ 3.0.0), foreach, doParallel, doRNG, robustbase, cellWise, VariableScreening, ggpubr, R.matlab |
| Published: |
2025-08-19 |
| DOI: |
10.32614/CRAN.package.spareg |
| Author: |
Laura Vana-Gür 
[aut, cre],
Roman Parzer
[aut],
Peter Filzmoser
[aut] |
| Maintainer: |
Laura Vana-Gür <laura.vana.guer at tuwien.ac.at> |
| BugReports: |
https://github.com/lauravana/spareg/issues |
| License: |
GPL-3 |
| URL: |
https://github.com/lauravana/spareg |
| NeedsCompilation: |
no |
| Citation: |
spareg citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
spareg results |