Gaussian Graphical Models Using Ridge Penalty Followed by Thresholding and Reestimation


[Up] [Top]

Documentation for package ‘GGMridge’ version 1.1

Help Pages

EM.mixture Estimation of the mixture distribution using EM algorithm
getEfronp Estimation of empirical null distribution.
GGMridge Gaussian Graphical Models Using Ridge Penalty Followed by Thresholding and Reestimation
ksStat The Kolmogorov-Smirnov Statistic for p-Values
lambda.cv Choose the Tuning Parameter of the Ridge Inverse
lambda.pcut.cv Choose the Tuning Parameter of the Ridge Inverse and Thresholding Level of the Empirical p-Values
lambda.pcut.cv1 Choose the Tuning Parameter of the Ridge Inverse and Thresholding Level of the Empirical p-Values.
lambda.TargetD Shrinkage Estimation of a Covariance Matrix Toward an Identity Matrix
ne.lambda.cv Choose the Tuning Parameter of a Ridge Regression Using Cross-Validation
R.separate.ridge Estimation of Partial Correlation Matrix Using p Separate Ridge Regressions.
scaledMat Scale a square matrix
simulateData Generate Simulation Data from a Random Network.
structuredEstimate Estimation of Partial Correlation Matrix Given Zero Structure.
transFisher Fisher's Z-Transformation