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-Gershgoren, Mantegna, & Ben-Jacob, 2010 <doi:10.1371/journal.pone.0015032>), Information Filtering Networks (Barfuss, Massara, Di Matteo, & Aste, 2016 <doi:10.1103/PhysRevE.94.062306>), and Efficiency-Cost Optimization (Fallani, Latora, & Chavez, 2017 <doi:10.1371/journal.pcbi.1005305>). 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), community-level network characteristics (e.g., community centrality), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
Version: 1.4.4 Depends: R (≥ 3.6.0) Imports: corrplot, doParallel, fdrtool, foreach, igraph, IsingFit, MASS, methods, parallel, pbapply, ppcor, psych, pwr, R.matlab, qgraph Suggests: googledrive Published: 2025-05-08 DOI: 10.32614/CRAN.package.NetworkToolbox Author: Alexander Christensen [aut, cre], Guido Previde Massara [ctb] Maintainer: Alexander Christensen <alexpaulchristensen at gmail.com> License: GPL (≥ 3.0) NeedsCompilation: no Citation: NetworkToolbox citation info Materials: NEWS In views: NetworkAnalysis, Psychometrics CRAN checks: NetworkToolbox results Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=NetworkToolbox to link to this page.
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