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.
- Version1.0.1
- R versionunknown
- LicenseGPL-2
- Needs compilation?Yes
- Ren et al. (2017)
- Ren et al.(2019)
- Last release02/22/2024
Documentation
Team
Jie Ren
Junhao Liu
Show author detailsRolesAuthorCen Wu
Show author detailsRolesAuthorLuann C. Jung
Show author detailsRolesAuthorYu Jiang
Show author detailsRolesAuthorYinhao Du
Show author detailsRolesAuthor
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