| ADdata | R-objects related to metabolomics data on patients with... |
| adjacentMat | Transform real matrix into an adjacency matrix |
| CNplot | Visualize the spectral condition number against the... |
| Communities | Search and visualize community-structures |
| conditionNumberPlot | Visualize the spectral condition number against the... |
| covML | Maximum likelihood estimation of the covariance matrix |
| covMLknown | Maximum likelihood estimation of the covariance matrix with... |
| createS | Simulate sample covariances or datasets |
| default.penalty | Construct commonly used penalty matrices |
| default.target | Generate a (data-driven) default target for usage in... |
| default.target.fused | Generate data-driven targets for fused ridge estimation |
| DiffGraph | Visualize the differential graph |
| dot-armaRidgeP | Core ridge precision estimators |
| edgeHeat | Visualize (precision) matrix as a heatmap |
| evaluateS | Evaluate numerical properties square matrix |
| evaluateSfit | Visual inspection of the fit of a regularized precision... |
| fullMontyS | Wrapper function |
| fused.test | Test the necessity of fusion |
| getKEGGPathway | Download KEGG pathway |
| GGMblockNullPenalty | Generate the distribution of the penalty parameter under the... |
| GGMblockTest | Test for block-indepedence |
| GGMmutualInfo | Mutual information between two sets of variates within a... |
| GGMnetworkStats | Gaussian graphical model network statistics |
| GGMnetworkStats.fused | Gaussian graphical model network statistics |
| GGMpathStats | Gaussian graphical model node pair path statistics |
| GGMpathStats.fused | Fused gaussian graphical model node pair path statistics |
| isSymmetricPD | Test for symmetric positive (semi-)definiteness |
| is.Xlist | Test if fused list-formats are correctly used |
| kegg.target | Construct target matrix from KEGG |
| KLdiv | Kullback-Leibler divergence between two multivariate normal... |
| KLdiv.fused | Fused Kullback-Leibler divergence for sets of distributions |
| loss | Evaluate regularized precision under various loss functions |
| momentS | Moments of the sample covariance matrix. |
| NLL | Evaluate the (penalized) (fused) likelihood |
| optPenalty.aLOOCV | Select optimal penalty parameter by approximate leave-one-out... |
| optPenalty.fused | Identify optimal ridge and fused ridge penalties |
| optPenalty.kCV | Select optimal penalty parameter by K-fold cross-validation |
| optPenalty.kCVauto | Automatic search for optimal penalty parameter |
| optPenalty.LOOCV | Select optimal penalty parameter by leave-one-out... |
| optPenalty.LOOCVauto | Automatic search for optimal penalty parameter |
| pcor | Compute partial correlation matrix or standardized precision... |
| plot.ptest | Plot the results of a fusion test |
| pooledS | Compute the pooled covariance or precision matrix estimate |
| print.optPenaltyFusedGrid | Print and plot functions for fused grid-based... |
| print.ptest | Print and summarize fusion test |
| pruneMatrix | Prune square matrix to those variables having nonzero entries |
| rags2ridges-package | Ridge estimation for high-dimensional precision matrices |
| ridgeP | Ridge estimation for high-dimensional precision matrices |
| ridgePathS | Visualize the regularization path |
| ridgeP.fused | Fused ridge estimation |
| ridgeS | Ridge estimation for high-dimensional precision matrices |
| rmvnormal | Multivariate Gaussian simulation |
| sparsify | Determine the support of a partial correlation/precision... |
| sparsify.fused | Determine support of multiple partial correlation/precision... |
| symm | Symmetrize matrix |
| Ugraph | Visualize undirected graph |
| Union | Subset 2 square matrices to union of variables having nonzero... |
