penalized: L1 (Lasso and Fused Lasso) and L2 (Ridge) Penalized Estimation
in GLMs and in the Cox Model
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
||DIFtree, GRridge, multiPIM, PACLasso, structree, subtype
||DIFboost, DIFlasso, GSelection, hdnom, mispr, mvdalab, pensim, predictionet, scRecover, splmm
||catdata, confSAM, fscaret, globaltest, lda, mlr, MWLasso, ordinalNet, peperr, riskRegression, tramnet
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