AlexChristensen/NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric Network Analysis
Version 1.1.3

Implements network analysis and graph theory measures used in neuroscience, cognitive science, and psychology. Methods include various filtering methods and approaches such as threshold, dependency (Kenett, Tumminello, Madi, Gur-Gershogoren, Mantegna, & Ben-Jacob, 2010 ), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 ), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 ). Brain methods include the recently developed Connectome Predictive Modeling (see references in package). Also implements several network measures including local network characteristics (e.g., centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.

Getting started

Package details

AuthorAlexander Christensen
MaintainerAlexander Christensen <[email protected]>
LicenseGPL (>= 3.0)
Version1.1.3
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("devtools")
library(devtools)
install_github("AlexChristensen/NetworkToolbox")
AlexChristensen/NetworkToolbox documentation built on May 6, 2018, 7:39 p.m.