Gaussian Graphical Models Using Ridge Penalty Followed by Thresholding and Reestimation

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Documentation for package ‘GGMridge’ version 1.5

• DESCRIPTION file.
• Package NEWS.

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