Fitting possibly high dimensional penalized regression models. The penalty structure can be any combination of an L1 penalty (lasso and fused lasso), an L2 penalty (ridge) and a positivity constraint on the regression coefficients. The supported regression models are linear, logistic and Poisson regression and the Cox Proportional Hazards model. Cross-validation routines allow optimization of the tuning parameters.
|Author||Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi, Matthew Lueder|
|License||GPL (>= 2)|
|Package repository||View on CRAN|
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