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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.

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conda 811.6 kB | win-64/r-penalized-0.9_53-r44hac2c72c_0.conda  8 months and 1 day ago 83 main
conda 810.8 kB | osx-64/r-penalized-0.9_53-r44hefbd7a6_0.conda  8 months and 1 day ago 62 main
conda 813.1 kB | win-64/r-penalized-0.9_53-r45hac2c72c_0.conda  8 months and 1 day ago 79 main
conda 811.5 kB | osx-64/r-penalized-0.9_53-r45hefbd7a6_0.conda  8 months and 1 day ago 65 main
conda 831.4 kB | linux-64/r-penalized-0.9_53-r45h3704496_0.conda  8 months and 1 day ago 596 main
conda 829.8 kB | linux-64/r-penalized-0.9_53-r44h3704496_0.conda  8 months and 1 day ago 633 main

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