Package: oddnet 0.1.1.2

Sevvandi Kandanaarachchi

oddnet: Anomaly Detection in Temporal Networks

Anomaly detection in dynamic, temporal networks. The package 'oddnet' uses a feature-based method to identify anomalies. First, it computes many features for each network. Then it models the features using time series methods. Using time series residuals it detects anomalies. This way, the temporal dependencies are accounted for when identifying anomalies (Kandanaarachchi, Hyndman 2022) <arxiv:2210.07407>.

Authors:Sevvandi Kandanaarachchi [aut, cre], Rob Hyndman [aut]

oddnet_0.1.1.2.tar.gz
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oddnet.pdf |oddnet.html
oddnet/json (API)

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

Bug tracker:https://github.com/sevvandi/oddnet/issues

Pkgdown site:https://sevvandi.github.io

On CRAN:

Conda:

4.22 score 3 stars 11 scripts 174 downloads 3 exports 58 dependencies

Last updated 10 months agofrom:c66aafdebb. Checks:4 OK, 5 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKApr 01 2025
R-4.5-winOKApr 01 2025
R-4.5-macOKApr 01 2025
R-4.5-linuxOKApr 01 2025
R-4.4-winNOTEApr 01 2025
R-4.4-macNOTEApr 01 2025
R-4.4-linuxNOTEApr 01 2025
R-4.3-winNOTEApr 01 2025
R-4.3-macNOTEApr 01 2025

Exports:anomalous_networkscompute_featureslad

Dependencies:anytimeBHclicolorspacecpp11digestdistributionaldplyrellipsisevdfablefabletoolsfansifarvergenericsggdistggplot2gluegtableigraphisobandlabelinglatticelifecyclelookoutlubridatemagrittrMASSMatrixmgcvmunsellmvtnormnlmenumDerivpcaPPpillarpkgconfigprogressrpurrrquadprogR6RANNRColorBrewerRcpprlangscalesstringistringrTDAstatstibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewithr

oddnet

Rendered fromoddnet.Rmdusingknitr::rmarkdownon Apr 01 2025.

Last update: 2022-12-19
Started: 2022-12-19