Package: spectralAnomaly 0.1.1.9000

spectralAnomaly: Detect Anomalies Using the Spectral Residual Algorithm
Apply the spectral residual algorithm to data, such as a time series, to detect anomalies. Anomaly scores can be used to determine outliers based upon a threshold or fed into more sophisticated prediction models. Methods are based upon "Time-Series Anomaly Detection Service at Microsoft", Ren, H., Xu, B., Wang, Y., et al., (2019) <doi:10.48550/arXiv.1906.03821>.
Authors:
spectralAnomaly_0.1.1.9000.tar.gz
spectralAnomaly_0.1.1.9000.zip(r-4.7)spectralAnomaly_0.1.1.9000.zip(r-4.6)spectralAnomaly_0.1.1.9000.zip(r-4.5)
spectralAnomaly_0.1.1.9000.tgz(r-4.6-any)spectralAnomaly_0.1.1.9000.tgz(r-4.5-any)
spectralAnomaly_0.1.1.9000.tar.gz(r-4.7-any)spectralAnomaly_0.1.1.9000.tar.gz(r-4.6-any)
spectralAnomaly_0.1.1.9000.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
spectralAnomaly/json (API)
NEWS
| # Install 'spectralAnomaly' in R: |
| install.packages('spectralAnomaly', repos = c('https://al-obrien.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/al-obrien/spectralanomaly/issues
Pkgdown/docs site:https://al-obrien.github.io
Last updated from:129cec94c2. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 104 | ||
| source / vignettes | OK | 129 | ||
| linux-release-x86_64 | NOTE | 110 | ||
| macos-release-arm64 | NOTE | 100 | ||
| macos-oldrel-arm64 | NOTE | 81 | ||
| windows-devel | NOTE | 66 | ||
| windows-release | NOTE | 76 | ||
| windows-oldrel | NOTE | 99 | ||
| wasm-release | OK | 84 |
Exports:add_anomalyanomaly_scoreanomaly_threshsaliency_map
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Generate anomalies within time series | add_anomaly |
| Create anomaly score from input data | anomaly_score |
| Apply threshold to anomaly score | anomaly_thresh |
| Create saliency map | saliency_map |
