Package: NetworkToolbox
Title: Methods and Measures for Brain, Cognitive, and Psychometric
        Network Analysis
Version: 1.2.3
Date: 2019-01-30
Author: Alexander Christensen
Maintainer: Alexander Christensen <alexpaulchristensen@gmail.com>
Description: 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), 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. 
Depends: R (>= 3.3.0)
License: GPL (>= 3.0)
Encoding: UTF-8
LazyData: true
Imports: Matrix, psych, corrplot, fdrtool, R.matlab, MASS, pwr, igraph,
        qgraph, ppcor, parallel, foreach, doParallel
RoxygenNote: 6.1.1
NeedsCompilation: no
Packaged: 2019-01-30 23:25:10 UTC; APCHRIST
Repository: CRAN
Date/Publication: 2019-01-31 05:43:16 UTC
