Adaptive LASSO and Network Regularized Generalized Linear Models

Efficient procedures for adaptive LASSO and network regularized for Gaussian, logistic, and Cox model. Provides network estimation procedure (combination of methods proposed by Ucar, et al. (2007) and Meinshausen and Buhlmann (2006) ), cross validation and stability selection proposed by Meinshausen and Buhlmann (2010) and Liu, Roeder and Wasserman (2010) methods. Interactive R app is available.


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install.packages("glmaag")

0.0.4 by Kaiqiao Li, 10 days ago


Browse source code at https://github.com/cran/glmaag


Authors: Kaiqiao Li [aut, cre] , Pei Fen Kuan [aut] , Xuefeng Wang [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports Rcpp, methods, stats, Matrix, ggplot2, gridExtra, maxstat, survminer, plotROC, shiny, foreach, pROC, huge, OptimalCutpoints

Depends on survival, data.table

Suggests knitr, rmarkdown

Linking to Rcpp, RcppArmadillo


See at CRAN