The package uses majorization minimization by coordinate descent (MMCD) algorithm to compute the solution surface for concave penalized logistic regression model. The SCAD and MCP (default) are two concave penalties considered in this implementation. For the MCP penalty, the package also provides the local linear approximation by coordinate descant (LLACD) and adaptive rescaling algorithms for computing the solutions. The package also provides a Lassoconcave hybrid penalty for fast variable selection. The hybrid penalty applies the concave penalty only to the variables selected by the Lasso. For all the implemented methods, the solution surface is computed along kappa, which is a more smooth fit for the logistic model. Tuning parameter selection method by kfold crossvalidated area under ROC curve (CVAUC) is implemented as well.
Package details 


Author  Dingfeng Jiang <dingfengjiang@gmail.com> 
Date of publication  20130318 10:29:02 
Maintainer  Dingfeng Jiang <dingfengjiang@gmail.com> 
License  GPL (>= 2) 
Version  3.10 
URL  http://www.rproject.org 
Package repository  View on CRAN 
Installation 
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