otsad: Online Time Series Anomaly Detectors

Implements a set of online fault detectors for time-series, called: PEWMA see M. Carter et al. (2012) <doi:10.1109/SSP.2012.6319708>, SD-EWMA and TSSD-EWMA see H. Raza et al. (2015) <doi:10.1016/j.patcog.2014.07.028>, KNN-CAD see E. Burnaev et al. (2016) <arXiv:1608.04585>, KNN-LDCD see V. Ishimtsev et al. (2017) <arXiv:1706.03412> and CAD-OSE see M. Smirnov (2018) <https://github.com/smirmik/CAD>. The first three algorithms belong to prediction-based techniques and the last three belong to window-based techniques. In addition, the SD-EWMA and PEWMA algorithms are algorithms designed to work in stationary environments, while the other four are algorithms designed to work in non-stationary environments.

Version: 0.1.0
Depends: R (≥ 3.4.0)
Imports: stats, ggplot2, plotly, sigmoid, reticulate
Suggests: testthat, stream, knitr, rmarkdown
Published: 2019-04-01
Author: Alaiñe Iturria [aut, cre], Jacinto Carrasco [aut], Francisco Herrera [aut], Santiago Charramendieta [aut], Karmele Intxausti [aut]
Maintainer: Alaiñe Iturria <aiturria at ikerlan.es>
BugReports: https://github.com/alaineiturria/otsad/issues
License: AGPL (≥ 3)
URL: https://github.com/alaineiturria/otsad
NeedsCompilation: no
SystemRequirements: Python (>= 3.0.1); bencode-python3 (1.0.2)
Citation: otsad citation info
Materials: README
In views: TimeSeries
CRAN checks: otsad results

Downloads:

Reference manual: otsad.pdf
Vignettes: The otsad Package: Online Time-Series Anomaly Detectors
Package source: otsad_0.1.0.tar.gz
Windows binaries: r-devel: otsad_0.1.0.zip, r-release: otsad_0.1.0.zip, r-oldrel: otsad_0.1.0.zip
OS X binaries: r-release: otsad_0.1.0.tgz, r-oldrel: otsad_0.1.0.tgz

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