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:
oddnet_0.1.1.2.tar.gz
oddnet_0.1.1.2.zip(r-4.5)oddnet_0.1.1.2.zip(r-4.4)oddnet_0.1.1.2.zip(r-4.3)
oddnet_0.1.1.2.tgz(r-4.4-any)oddnet_0.1.1.2.tgz(r-4.3-any)
oddnet_0.1.1.2.tar.gz(r-4.5-noble)oddnet_0.1.1.2.tar.gz(r-4.4-noble)
oddnet_0.1.1.2.tgz(r-4.4-emscripten)oddnet_0.1.1.2.tgz(r-4.3-emscripten)
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
Last updated 6 months agofrom:c66aafdebb. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 02 2024 |
R-4.5-win | OK | Nov 02 2024 |
R-4.5-linux | OK | Nov 02 2024 |
R-4.4-win | OK | Nov 02 2024 |
R-4.4-mac | OK | Nov 02 2024 |
R-4.3-win | OK | Nov 02 2024 |
R-4.3-mac | OK | Nov 02 2024 |
Exports:anomalous_networkscompute_featureslad
Dependencies:anytimeBHclicolorspacecpp11digestdistributionaldplyrellipsisevdfablefabletoolsfansifarvergenericsggdistggplot2gluegtableigraphisobandlabelinglatticelifecyclelookoutlubridatemagrittrMASSMatrixmgcvmunsellmvtnormnlmenumDerivpcaPPpillarpkgconfigprogressrpurrrquadprogR6RANNRColorBrewerRcpprlangscalesstringistringrTDAstatstibbletidyrtidyselecttimechangetsibbleutf8vctrsviridisLitewithr