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Network-based regularization has achieved success in variable selection for high-dimensional biological data due to its ability to incorporate correlations among genomic features. This package provides procedures of network-based variable selection for generalized linear models (Ren et al. (2017) <doi:10.1186/s12863-017-0495-5> and Ren et al.(2019) <doi:10.1002/gepi.22194>). Continuous, binary, and survival response are supported. Robust network-based methods are available for continuous and survival responses.
| Version: | 1.0.1 |
| Depends: | R (≥ 4.0.0) |
| Imports: | glmnet, stats, Rcpp, igraph, utils |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat, covr |
| Published: | 2024-02-22 |
| DOI: | 10.32614/CRAN.package.regnet |
| Author: | Jie Ren, Luann C. Jung, Yinhao Du, Cen Wu, Yu Jiang, Junhao Liu |
| Maintainer: | Jie Ren <jieren at ksu.edu> |
| BugReports: | https://github.com/jrhub/regnet/issues |
| License: | GPL-2 |
| URL: | https://github.com/jrhub/regnet |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| In views: | Omics |
| CRAN checks: | regnet results |
| Reference manual: | regnet.pdf |
| Package source: | regnet_1.0.1.tar.gz |
| Windows binaries: | r-devel: regnet_1.0.1.zip, r-release: regnet_1.0.1.zip, r-oldrel: regnet_1.0.1.zip |
| macOS binaries: | r-release (arm64): regnet_1.0.1.tgz, r-oldrel (arm64): regnet_1.0.1.tgz, r-release (x86_64): regnet_1.0.1.tgz, r-oldrel (x86_64): regnet_1.0.1.tgz |
| Old sources: | regnet archive |
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These binaries (installable software) and packages are in development.
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