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This is an implementation of the partial profile score feature selection (PPSFS) approach to generalized linear (interaction) models. The PPSFS is highly scalable even for ultra-high-dimensional feature space. See the paper by Xu, Luo and Chen (2021, <doi:10.4310/21-SII706>).
| Version: | 0.1.0 |
| Imports: | Rcpp, brglm2 |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2022-03-21 |
| Author: | Zengchao Xu [aut, cre], Shan Luo [aut], Zehua Chen [aut] |
| Maintainer: | Zengchao Xu <zengc.xu at aliyun.com> |
| BugReports: | https://github.com/paradoxical-rhapsody/PPSFS/issues |
| License: | GPL-3 |
| URL: | https://github.com/paradoxical-rhapsody/PPSFS |
| NeedsCompilation: | yes |
| Language: | en-US |
| Materials: | README NEWS |
| CRAN checks: | PPSFS results |
| Reference manual: | PPSFS.pdf |
| Package source: | PPSFS_0.1.0.tar.gz |
| Windows binaries: | r-devel: PPSFS_0.1.0.zip, r-release: PPSFS_0.1.0.zip, r-oldrel: PPSFS_0.1.0.zip |
| macOS binaries: | r-release (arm64): PPSFS_0.1.0.tgz, r-oldrel (arm64): PPSFS_0.1.0.tgz, r-release (x86_64): PPSFS_0.1.0.tgz, r-oldrel (x86_64): PPSFS_0.1.0.tgz |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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