| pdglasso-package | pdglasso: Graphical Lasso for Coloured Gaussian Graphical Models for Paired Data |
| admm.pdglasso | ADMM graphical lasso algorithm for pdRCON models |
| bc_data | Breast Cancer dataset |
| compute.eBIC | Extended Bayesian Information Criterion (eBIC) for pdRCON models |
| fMRI_parietal | fMRI dataset |
| GGM.simulate | Random simulation of Gaussian graphical models (GGMs) |
| lams.max | Maximum theoretical values of lambda1 and lambda2 |
| pdColG.get | pdColG matrix from the output of a call to 'admm.pdglasso' |
| pdglasso | pdglasso: Graphical Lasso for Coloured Gaussian Graphical Models for Paired Data |
| pdRCON.mle | Maximum likelihood estimate of a pdRCON model |
| pdRCON.select | Selection and estimate of a pdRCON model according to eBIC |
| pdRCON.simulate | Random simulation of pdRCON models |
| plot.ADMMoutput | Diagnostic plot for the output of the ADMM |
| plot.pdColG | Visual representation of a coloured graph for paired data |
| summary.pdColG | Structural properties of a coloured graph for paired data |
| toy_data | Toy dataset generated by a call to the 'pdRCON.simulate' function |