End-to-End Sparse Gaussian Graphical Model Simulation, Estimation, Visualization, Evaluation and Application

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Documentation for package ‘JointNets’ version 2.0.1

Help Pages

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
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
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
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
QDA_eval graphical model model evaluation using QDA as a classifier
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