Network-Based Regularization for Generalized Linear Models
k-folds cross-validation for regnet
plot a regnet object
print a cv.regnet object
print a regnet object
regnet: Network-Based Regularization for Generalized Linear Models
fit a regression for given lambda with network-based regularization
Example datasets for demonstrating the features of regnet
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.