Package: NetOrigin 1.1-6

NetOrigin: Origin Estimation for Propagation Processes on Complex Networks

Performs network-based source estimation. Different approaches are available: effective distance median, recursive backtracking, and centrality-based source estimation. Additionally, we provide public transportation network data as well as methods for data preparation, source estimation performance analysis and visualization.

Authors:Juliane Manitz [aut, cre], Jonas Harbering [ctb], Jun Li [ctb]

NetOrigin_1.1-6.tar.gz
NetOrigin_1.1-6.zip(r-4.7)NetOrigin_1.1-6.zip(r-4.6)NetOrigin_1.1-6.zip(r-4.5)
NetOrigin_1.1-6.tgz(r-4.6-any)NetOrigin_1.1-6.tgz(r-4.5-any)
NetOrigin_1.1-6.tar.gz(r-4.7-any)NetOrigin_1.1-6.tar.gz(r-4.6-any)
NetOrigin_1.1-6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
NetOrigin/json (API)

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

Bug tracker:https://github.com/jmanitz/netorigin/issues

Pkgdown/docs site:https://netorigin.manitz.org

Datasets:
  • delayAth - Delay propagation data examples simulated by LinTim software
  • delayGoe - Delay propagation data examples simulated by LinTim software
  • ptnAth - Public transportation network datasets from LinTim software
  • ptnGoe - Public transportation network datasets from LinTim software

On CRAN:

Conda:

2.74 score 11 scripts 149 downloads 20 exports 69 dependencies

Last updated from:30ecd39b40. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64NOTE140
source / vignettesOK178
linux-release-x86_64NOTE132
macos-release-arm64NOTE116
macos-oldrel-arm64NOTE92
windows-develNOTE83
windows-releaseNOTE109
windows-oldrelNOTE89
wasm-releaseOK125

Exports:aggr_dataanalyze_ptncompute_mu_lambdaeff_dijkstraeff_distinitial_condition_sib_modeloriginorigin_backtrackingorigin_bayesianorigin_centralityorigin_edmorigin_multipleperformanceplot_performanceplot_ptnread_DB_datarobustnessspd_dijkstrastochastic_sib_modelvar_wtd_mean_cochran

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercolorspacecorpcorcpp11data.tabledigestdplyrevaluatefarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsigraphisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMatrixmemoisemimemvtnormnnetpillarpkgconfigplyrR6rappdirsRColorBrewerRcpprlangrmarkdownrpartrstudioapiS7sassscalesstringistringrtibbletidyselecttinytexutf8vctrsviridisLitewithrxfunyaml

Readme and manuals

Help Manual

Help pageTopics
convert individual event information to aggregated information per network nodeaggr_data
analyze public transportation network characteristicsanalyze_ptn
Compute Mu and Lambda for Source Detection Functioncompute_mu_lambda
Delay propagation data examples simulated by LinTim softwaredelay-data delayAth delayGoe
Computation of effective path distanceeff_dijkstra eff_dist spd_dijkstra
Provide Initial Condition for Function SIB_SSinitial_condition_sib_model
Origin Estimation for Propagation Processes on Complex NetworksNetOrigin-package NetOrigin
Origin Estimation for Propagation Processes on Complex Networksorigin origin_backtracking origin_bayesian origin_centrality origin_edm
Multiple origin estimation using community partitioningorigin_multiple
methods for origin estimation objects of class 'origin'origin-methods performance.origin plot.origin print.origin summary.origin
generic method for performance evaluationperformance
A plot method combining a time series of performance results.plot_performance
A plot method for public transportation networks (PTNs).plot_ptn
Public transportation network datasets from LinTim software (Integrated Optimization in Public Transportation)ptn-data ptnAth ptnGoe
Reads a data file as provided by 'Deutsche Bahn' (for internal use).read_DB_data
run robustness analysis for a source estimate by subsampling individual events.robustness
methods for robustness estimation objects of class 'robustness'plot plot.robustness print.robustness robustness-methods summary summary.robustness
Stochastic SIB model for infected cases simulationstochastic_sib_model
Computes the variance of a weighted mean following the definition by Cochran (1977; see Gatz and Smith, 1995)var_wtd_mean_cochran