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:Allen OBrien [aut, cre, cph]

spectralAnomaly_0.1.1.9000.tar.gz
spectralAnomaly_0.1.1.9000.zip(r-4.7-any)spectralAnomaly_0.1.1.9000.zip(r-4.6-any)spectralAnomaly_0.1.1.9000.zip(r-4.5-any)
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✨
DESCRIPTION |NEWS
card.svg |card.png
spectralAnomaly/json (API)

# 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

On CRAN:

Conda:

3.00 score 2 stars 5 scripts 175 downloads 4 exports 0 dependencies

Last updated from:129cec94c2. Checks:7 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-develNOTE148
source / vignettesOK168
linux-releaseNOTE107
macos-releaseNOTE146
macos-oldrelNOTE122
windows-develNOTE69
windows-releaseNOTE53
windows-oldrelNOTE63
wasm-releaseOK88

Exports:add_anomalyanomaly_scoreanomaly_threshsaliency_map

Dependencies: