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.
Version:
0.9-53
Depends:
R (≥ 2.10.0),
survival, methods
Published:
2025年10月02日
Author:
Jelle Goeman [aut, cre],
Rosa Meijer [aut],
Nimisha Chaturvedi [aut],
Matthew Lueder [aut]
Maintainer:
Jelle Goeman <j.j.goeman at lumc.nl>
NeedsCompilation:
yes
Documentation:
Downloads:
Reverse dependencies:
Reverse imports:
c060,
DIFboost,
DIFlasso,
flassomsm,
GSelection,
hdnom,
mispr,
mvdalab,
penalizedclr,
pensim,
scRecover,
splmm
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