Package: NetworkToolbox 1.4.3

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-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.

Authors:Alexander Christensen [aut, cre], Guido Previde Massara [ctb]

NetworkToolbox_1.4.3.tar.gz
NetworkToolbox_1.4.3.zip(r-4.5)NetworkToolbox_1.4.3.zip(r-4.4)NetworkToolbox_1.4.3.zip(r-4.3)
NetworkToolbox_1.4.3.tgz(r-4.4-any)NetworkToolbox_1.4.3.tgz(r-4.3-any)
NetworkToolbox_1.4.3.tar.gz(r-4.5-noble)NetworkToolbox_1.4.3.tar.gz(r-4.4-noble)
NetworkToolbox_1.4.3.tgz(r-4.4-emscripten)NetworkToolbox_1.4.3.tgz(r-4.3-emscripten)
NetworkToolbox.pdf |NetworkToolbox.html
NetworkToolbox/json (API)
NEWS

# Install 'NetworkToolbox' in R:
install.packages('NetworkToolbox', repos = c('https://alexchristensen.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/alexchristensen/networktoolbox/issues

Datasets:
  • behavOpen - NEO-PI-3 for Resting-state Data
  • neoOpen - NEO-PI-3 Openness to Experience Data
  • openness - Four Inventories of Openness to Experience
  • openness.key - Four Inventories of Openness to Experience

On CRAN:

network-analysis

6.85 score 21 stars 3 packages 99 scripts 1.9k downloads 4 mentions 66 exports 102 dependencies

Last updated 2 years agofrom:3fe11eb753. Checks:OK: 1 NOTE: 5 ERROR: 1. Indexed: yes.

TargetResultDate
Doc / VignettesOKOct 27 2024
R-4.5-winERROROct 27 2024
R-4.5-linuxNOTEOct 27 2024
R-4.4-winNOTEOct 27 2024
R-4.4-macNOTEOct 27 2024
R-4.3-winNOTEOct 27 2024
R-4.3-macNOTEOct 27 2024

Exports:adapt.abetweennessbinarizeclosenessclustcoeffcomcatcomm.closecomm.eigencomm.strconnconvert2igraphconvertConnBrainMatcor2covcore.itemscpmEVcpmFPcpmFPpermcpmIVcpmIVpermcpmPlotdCordCor.paralleldegreedependdepnadescdesc.alldistancediversityECOECOplusMaSTedgerepeigenvectorflow.fracgatewaygfcnv_logdethybridimpactis.graphicalkldlattnetleverageLoGolouvainMaSTMFCFnet.coveragenetwork.coveragenetwork.permutationneuralnetfilterparticipationpathlengthsrandnetregresp.reprmserspbcsim.chordalsim.swnsmallworldnessstablestrengththresholdTMFGtransitivityun.direct

Dependencies:abindbackportsbase64encbslibcachemcheckmatecliclustercodetoolscolorspacecorpcorcorrplotcpp11data.tabledigestdoParallelevaluatefansifarverfastmapfdrtoolfontawesomeforeachforeignFormulafsggplot2glassoglmnetglueGPArotationgridExtragtablegtoolshighrHmischtmlTablehtmltoolshtmlwidgetsigraphIsingFitisobanditeratorsjpegjquerylibjsonliteknitrlabelinglatticelavaanlifecyclemagrittrMASSMatrixmemoisemgcvmimemnormtmunsellnlmennetnumDerivpbapplypbivnormpillarpkgconfigplyrpngppcorpsychpwrqgraphquadprogR.matlabR.methodsS3R.ooR.utilsR6rappdirsRColorBrewerRcppRcppEigenreshape2rlangrmarkdownrpartrstudioapisassscalesshapestringistringrsurvivaltibbletinytexutf8vctrsviridisviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
NetworkToolbox-packageNetworkToolbox-package NetworkToolbox
Adaptive Alphaadapt.a
NEO-PI-3 for Resting-state DatabehavOpen
Betweenness Centralitybetweenness
Binarize Networkbinarize
Closeness Centralitycloseness
Clustering Coefficientclustcoeff
Communicating Nodescomcat
Community Closeness Centralitycomm.close
Community Eigenvector Centralitycomm.eigen
Community Strength/Degree Centralitycomm.str
Network Connectivityconn
Convert Network(s) to igraph's Formatconvert2igraph
Import CONN Toolbox Brain Matrices to R formatconvertConnBrainMat
Convert Correlation Matrix to Covariance Matrixcor2cov
Core Itemscore.items
Connectome-based Predictive Modelingcpm cpmEV cpmFP cpmFPperm cpmIV cpmIVperm cpmPlot
Distance Correlation for ROI Time SeriesdCor
Parallelization of Distance Correlation for ROI Time SeriesdCor.parallel
Degreedegree
Dependency Network Approachdepend
Dependency Neural Networksdepna
Variable Descriptive Statisticsdesc
Dataset Descriptive Statisticsdesc.all
Distancedistance
Diversity Coefficientdiversity
ECO Neural Network FilterECO
ECO+MaST Network FilterECOplusMaST
Edge Replicationedgerep
Eigenvector Centralityeigenvector
Flow Fractionflow.frac
MFCF Gain Functionsgain.functions gdcnv_lmfit gfcnv_logdet gfcnv_logdet_val
Gateway Coefficientgateway
Hybrid Centralityhybrid
Node Impactimpact
Determines if Network is Graphicalis.graphical
Kullback-Leibler Divergencekld
Generates a Lattice Networklattnet
Leverage Centralityleverage
Local/Global Inversion MethodLoGo
Louvain Community Detection Algorithmlouvain
Maximum Spanning TreeMaST
Maximally Filtered Clique ForestMFCF
NEO-PI-3 Openness to Experience DataneoOpen
Network Coveragenet.coverage
Network Coveragenetwork.coverage
Permutation Test for Network Measuresnetwork.permutation
Neural Network Filterneuralnetfilter
Four Inventories of Openness to Experienceopenness openness.key
Participation Coefficientparticipation
Characteristic Path Lengthspathlengths
Plots CPM resultsplot.cpm
Generates a Random Networkrandnet
Regression Matrixreg
Repeated Responses Checkresp.rep
Root Mean Square Errorrmse
Randomized Shortest Paths Betweenness Centralityrspbc
Simulate Chordal Networksim.chordal
Simulate Small-world Networksim.swn
Small-worldness Measuresmallworldness
Stabilizing Nodesstable
Node Strengthstrength
Threshold Network Estimation Methodsthreshold
Triangulated Maximally Filtered GraphTMFG
Transitivitytransitivity
Convert Directed Network to Undirected Networkun.direct