Gaussian Graphical Models Using Ridge Penalty Followed by Thresholding and Reestimation


[Up] [Top]

Documentation for package ‘GGMridge’ version 1.4

Help Pages

EM.mixture Estimation of the mixture distribution using EM algorithm
getEfronp Estimation of empirical null distribution.
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. Calculate total prediction error for test data after fitting partial correlations from train data for all values of lambda and pcut.
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