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regnet

Network-Based Regularization for Generalized Linear Models

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.

Versions across snapshots

VersionRepositoryFileSize
1.0.2 rolling linux/jammy R-4.5 regnet_1.0.2.tar.gz 2.5 MiB
1.0.2 rolling linux/noble R-4.5 regnet_1.0.2.tar.gz 2.5 MiB
1.0.2 rolling source/ R- regnet_1.0.2.tar.gz 2.3 MiB
1.0.2 latest linux/jammy R-4.5 regnet_1.0.2.tar.gz 2.5 MiB
1.0.2 latest linux/noble R-4.5 regnet_1.0.2.tar.gz 2.5 MiB
1.0.2 latest source/ R- regnet_1.0.2.tar.gz 2.3 MiB
1.0.2 2026-04-26 source/ R- regnet_1.0.2.tar.gz 2.3 MiB
1.0.2 2026-04-23 source/ R- regnet_1.0.2.tar.gz 2.3 MiB
1.0.2 2026-04-09 windows/windows R-4.5 regnet_1.0.2.zip 2.9 MiB
1.0.2 2025-04-20 source/ R- regnet_1.0.2.tar.gz 2.3 MiB

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