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anomaly

Fast anomaly detection in R

In Brief

This R package implements CAPA (Collective And Point Anomalies) introduced by Fisch, Eckley and Fearnhead (2018). The package is available on CRAN and contains lightcurve data from the Kepler telescope to illustrate the algorithm.

About CAPA

CAPA detects and distinguishes between collective and point anomalies. The algorithm's runtime scales linearly at best and quadratically at worst in the number of datapoints. It is coded in C and can process 10000 datapoints almost instantly.

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Version

Install

install.packages('anomaly')

Monthly Downloads

402

Version

2.0.4

License

GPL

Maintainer

Daniel Grose

Last Published

February 28th, 2020

Functions in anomaly (2.0.4)

ac_corrected

Transforms the data X to account for autocorrelation.
robustscale

robustscale
show

Displays S4 objects produced by capa methods.
capa

A technique for detecting anomalous segments and points based on CAPA.
capa.mv

Detection of multivariate anomalous segments and points using MVCAPA.
pass

Detection of multivariate anomalous segments using PASS.
plot

Visualisation of data, collective and point anomalies.
period_average

A function to search the Kepler data for periodically recurring dips in luminosity.
point_anomalies

Point anomaly location and strength.
simulate

A function for generating simulated multivariate data
summary

Summary of collective and point anomalies.
capa.uv

Detection of univariate anomalous segments and points using CAPA.
collective_anomalies

Collective anomaly location, lags, and mean/variance changes.
machinetemp

Machine temperature data.
Lightcurves

Kepler Lightcurve data.
anomaly_series

A technique for detecting anomalous segments based on CAPA.