Package: penalized 0.9-52

Jelle Goeman

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 parameters.

Authors:Jelle Goeman, Rosa Meijer, Nimisha Chaturvedi, Matthew Lueder

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28 exports 3 stars 3.26 score 5 dependencies 15 dependents 5 mentions 363 scripts 2.2k downloads

Last updated 2 years agofrom:054894f8cf. Checks:OK: 1 NOTE: 8. Indexed: no.

Exports:as.data.frameas.listas.matrixbasehazbasesurvcoefcoefficientscontr.diffcontr.nonecvlfittedfitted.valueslinear.predictorsloglikoptL1optL2penalizedpenaltyplotplotpathpredictprofL1profL2residualsshowsurvivaltimeweights

Dependencies:latticeMatrixRcppRcppArmadillosurvival