genRidgePenaltyMat      Penalty parameter matrix for generalized ridge
                        regression.
makeFoldsGLMcv          Generate folds for cross-validation of
                        generalized linear models.
optPenaltyGGMmixture.kCVauto
                        Automatic search for optimal penalty parameter
                        (mixture of GGMs).
optPenaltyGLM.kCVauto   Automatic search for optimal penalty parameters
                        of the targeted ridge GLM estimator.
optPenaltyGLMmultiT.kCVauto
                        Automatic search for optimal penalty parameters
                        of the targeted ridge GLM estimator.
optPenaltyPgen.kCVauto.banded
                        Automatic search for optimal penalty parameter
                        (generalized ridge precision).
optPenaltyPgen.kCVauto.groups
                        Automatic search for optimal penalty parameter
                        (generalized ridge precision).
optPenaltyPmultiT.kCVauto
                        Automatic search for optimal penalty parameter
                        (ridge precision with multi-targets).
optPenaltyPrep.kCVauto
                        Automatic search for optimal penalty parameters
                        (for precision estimation of data with
                        replicates).
optPenaltyPrepEdiag.kCVauto
                        Automatic search for optimal penalty parameters
                        (for precision estimation of data with
                        replicates).
porridge-package        Ridge-Type Penalized Estimation of a Potpourri
                        of Models.
ridgeGGMmixture         Ridge penalized estimation of a mixture of
                        GGMs.
ridgeGLM                Ridge estimation of generalized linear models.
ridgeGLMdof             Degrees of freedom of the generalized ridge
                        estimator.
ridgeGLMmultiT          Multi-targeted ridge estimation of generalized
                        linear models.
ridgePgen               Ridge estimation of the inverse covariance
                        matrix with element-wise penalization and
                        shrinkage.
ridgePgen.kCV           K-fold cross-validated loglikelihood of ridge
                        precision estimator.
ridgePgen.kCV.banded    K-fold cross-validated loglikelihood of ridge
                        precision estimator for banded precisions.
ridgePgen.kCV.groups    K-fold cross-validated loglikelihood of ridge
                        precision estimator with group-wise penalized
                        variates.
ridgePmultiT            Ridge estimation of the inverse covariance
                        matrix with multi-target shrinkage.
ridgePrep               Ridge penalized estimation of the precision
                        matrix from data with replicates.
ridgePrepEdiag          Ridge penalized estimation of the precision
                        matrix from data with replicates.
