penalized (0.9-51)

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 parameters.

Maintainer: ORPHANED
Author(s): Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi, Matthew Lueder

License: GPL (>= 2)

Uses: Rcpp, survival
Reverse depends: DIFtree, lmmlasso, multiPIM, PACLasso, pensim, structree, subtype
Reverse suggests: caret, catdata, confSAM, fscaret, Grace, lda, mlr, mlr3proba, MWLasso, ordinalNet, peperr, riskRegression, tramnet

Released almost 2 years ago.