NetworkToolbox: Methods and Measures for Brain, Cognitive, and Psychometric
Network Analysis
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 <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), global network characteristics (e.g., clustering coefficient), and various other measures associated with the reliability and reproducibility of network analysis.
| Version: |
1.1.2 |
| Depends: |
R (≥ 3.3.0) |
| Imports: |
Matrix, psych, corrplot, fdrtool, R.matlab, MASS, pwr, igraph, qgraph, IsingFit, ppcor, parallel, foreach, doSNOW |
| Published: |
2018-04-29 |
| Author: |
Alexander Christensen |
| Maintainer: |
Alexander Christensen <alexpaulchristensen at gmail.com> |
| License: |
GPL (≥ 3.0) |
| NeedsCompilation: |
no |
| Citation: |
NetworkToolbox citation info |
| Materials: |
NEWS |
| CRAN checks: |
NetworkToolbox results |
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Reverse dependencies:
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