ABIDE_aal116_timeseries
                        ABIDE I preprocessed time series grouped by
                        control and autism and partitioned by AAL116
                        atlas
AUC                     return AUC score for JointNets method
BIC                     calculate BIC score for JointNets method
F1                      Compute F1 score for JointNets result
F1.diffee               computes F1 score for jointnet result
F1.jeek                 computes F1 score for jointnet result
F1.kdiffnet             computes F1 score for jointnet result
F1.simule               computes F1 score for jointnet result
F1.wsimule              computes F1 score for jointnet result
QDA_eval                graphical model model evaluation using QDA as a
                        classifier
aal116coordinates       AAL116 brain atlas coordinates in MNI space
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
cancer                  Microarray data set for breast cancer
compute_cov             helper function to add compute covariance
                        matrix / kendall tau correlation matrix
diffee                  Fast and Scalable Learning of Sparse Changes in
                        High-Dimensional Gaussian Graphical Model
dimension_reduce        reduce the dimensionality of the datalist if
                        needed
exampleData             A simulated toy dataset that includes 2 data
                        matrices (from 2 related tasks).
exampleDataGraph        A simulated toy dataset that includes 3 igraph
                        objects
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
jgl                     wrapper for function JGL fromo package "JGL"
jointplot               core function to plot
kdiffnet                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
nip_37_data             NIPS word count dataset
plot.diffee             plot diffee result specified by user input
plot.jeek               Plot jeek result specified by user input
plot.jgl                Plot jgl result specified by user input
plot.kdiffnet           plot kdiffnet 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
plot_brain              plot 3d brain network from JointNets result
plot_brain.diffee       plot 3d brain network from diffee result
plot_brain.jeek         plot 3d brain network from jeek result
plot_brain.jgl          plot 3d brain network from jgl result
plot_brain.kdiffnet     plot 3d brain network from kdiffnet result
plot_brain.simule       plot 3d brain network from simule result
plot_brain.wsimule      plot 3d brain network from wsimule result
plot_brain_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.jeek        return igraph object from jeek result specified
                        by user input
returngraph.jgl         return igraph object from jgl result specified
                        by user input
returngraph.kdiffnet    return igraph object from kdiffnet 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
train_valid_test_split
                        split a datalist to train,validation and test
wsimule                 A constrained and weighted l1 minimization
                        approach for estimating multiple Sparse
                        Gaussian or Nonparanormal Graphical Models
