| aal116coordinates | AAL116 brain atlas coordinates in MNI space |
| ABIDE_aal116_timeseries | ABIDE I preprocessed time series grouped by control and autism and partitioned by AAL116 atlas |
| add_name_to_out | helper function to add row/col names to JointNets precision matrix output To help label igraph object in returngraph and plot |
| AUC | return AUC score for JointNets method |
| BIC | calculate BIC score for JointNets method |
| cancer | Microarray data set for breast cancer |
| diffee | Fast and Scalable Learning of Sparse Changes in High-Dimensional Gaussian Graphical Model Structure |
| diffeek | Fast and Scalable Estimator for Using Additional Knowledge in Learning Sparse Structure Change of High Dimensional of Sparse Changes in High-Dimensional Gaussian Graphical Models |
| exampleData | A simulated toy dataset that includes 2 data matrices (from 2 related tasks). |
| exampleDataGraph | A simulated toy dataset that includes 3 igraph objects |
| F1 | Compute F1 score for JointNets result |
| F1.diffee | computes F1 score for jointnet result |
| F1.diffeek | computes F1 score for jointnet result |
| F1.fasjem | computes F1 score for jointnet result |
| F1.jeek | computes F1 score for jointnet result |
| F1.simule | computes F1 score for jointnet result |
| F1.wsimule | computes F1 score for jointnet result |
| fasjem | A Fast and Scalable Joint Estimator for Learning Multiple Related Sparse Gaussian Graphical Models |
| generateSampleList | function to generate a list of samples from simulatedGraph result |
| generateSamples | function to generate samples from a single precision matrix |
| jeek | A Fast and Scalable Joint Estimator for Integrating Additional Knowledge in Learning Multiple Related Sparse Gaussian Graphical Models |
| jointplot | core function to plot |
| nip_37_data | NIPS word count dataset |
| plot.diffee | plot diffee result specified by user input |
| plot.diffeek | plot diffeek result specified by user input |
| plot.fasjem | Plot fasjem result specified by user input |
| plot.jeek | Plot jeek result specified by user input |
| plot.simulation | Plot simulatedgraph result (generated from function simulation()) (class simulation) |
| plot.simule | Plot simule result specified by user input |
| plot.wsimule | Plot wsimule result specified by user input |
| plotbrain | plot 3d brain network from JointNets result |
| plotbrain.diffee | plot 3d brain network from diffee result |
| plotbrain.diffeek | plot 3d brain network from diffeek result |
| plotbrain.fasjem | plot 3d brain network from fasjem result |
| plotbrain.jeek | plot 3d brain network from jeek result |
| plotbrain.simule | plot 3d brain network from simule result |
| plotbrain.wsimule | plot 3d brain network from wsimule result |
| plotbrain_joint | plot 3d brain network |
| plot_gui | GUI of JointNets plot |
| returngraph | return igraph object from jointnet result specified by user input |
| returngraph.diffee | return igraph object from diffee result specified by user input |
| returngraph.diffeek | return igraph object from diffee result specified by user input |
| returngraph.fasjem | return igraph object from fasjem result specified by user input |
| returngraph.jeek | return igraph object from jeek result specified by user input |
| returngraph.simulation | return igraph object from simulation result specified by user input |
| returngraph.simule | return igraph object from simule result specified by user input |
| returngraph.wsimule | return igraph object from wsimule result specified by user input |
| simulateGraph | function to simulate multiple sparse graphs |
| simulation | simulate multiple sparse graphs and generate samples |
| simule | A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models Estimate multiple, related sparse Gaussian or Nonparanormal graphical |
| wsimule | A constrained and weighted l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models |