Hypothesis Testing for Populations of Brain Networks

Documentation for package ‘BrainNetTest’ version 0.2.2

compute_central_graph	Compute the Central (Representative) Graph for a Population
compute_distance	Compute the Manhattan Norm Distance Between Two Graphs
compute_edge_frequencies	Compute Edge Frequencies in Populations
compute_edge_pvalues	Compute P-Values for Edge Differences Between Populations
compute_test_statistic	Compute the Test Statistic T for Brain Network Populations
generate_category_graphs	Generate a Set of Graphs with Similar Community Structures for a Category
generate_community_graph	Generate a Random Symmetric Adjacency Matrix with Community Structure
generate_random_graph	Generate a Random Symmetric Adjacency Matrix
get_critical_nodes	Extract Critical Nodes from Critical Edge Results
global_test	Permutation Test for Differences Between Populations of Brain Networks
identify_critical_links	Identify Critical Edges That Explain Population Differences
plot.critical_links	Plot a Critical-Edge Analysis
plot_critical_edges	Visualize Central Graphs and Critical Edges
print.critical_links	Print a Critical-Edge Analysis
print.global_test	Print a Global Test Result
print.summary.critical_links	Print a Critical-Edge Analysis Summary
rank_edges	Rank Edges Based on P-Values
summary.critical_links	Summarise a Critical-Edge Analysis