Package: shrink
Type: Package
Title: Global, Parameterwise, and Joint Shrinkage of Regression
        Coefficients
Version: 1.0
Date: 2013-04-03
Author: Daniela Dunkler, Georg Heinze
Maintainer: Daniela Dunkler <daniela.dunkler@meduniwien.ac.at>
Description: Shrinkage of regression coefficients in prognostic models
        is required to correct the optimism in such a model caused by
        variable selection. While global shrinkage modifies all
        regression coefficients by the same factor, parameterwise
        shrinkage factors differ between regression coefficients, their
        values depending on each variable's prognostic relevance.  With
        highly correlated or semantically related variables, such as
        several columns of a design matrix describing a non-linear
        effect, a compromise between global, and parameterwise
        shrinkage, termed 'joint shrinkage', is a useful extension.  A
        computational shortcut to resampling-based shrinkage factor
        estimation based on DFBETA residuals is applied.  Global,
        parameterwise, and joint shrinkage for models fitted by lm,
        glm, coxph, or mfp is available.
Suggests: survival, mfp, MASS
License: GPL
Packaged: 2013-04-02 13:27:45 UTC; Daniela
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2013-04-02 16:08:44