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.
Documentation: Downloads: Reverse dependencies: Reverse depends: DIFtree, structree Reverse imports: c060, DIFboost, DIFlasso, GSelection, hdnom, mispr, mvdalab, penalizedclr, pensim, scRecover, splmm Reverse suggests: catdata, confSAM, flowml, fscaret, globaltest, lda, mlr, ordinalNet, peperr, riskRegression, tramnet Linking:Please use the canonical form https://CRAN.R-project.org/package=penalized to link to this page.
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