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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

655

Version

2.0.1

License

GPL

Maintainer

Daniel Grose

Last Published

September 11th, 2019

Functions in anomaly (2.0.1)

capa

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

A function for generating simulated multivariate data
Lightcurves

Kepler Lightcurve data.
machinetemp

Machine temperature data.
summary

Summary of collective and point anomalies.
capa.mv

Detection of multivariate anomalous segments and points using MVCAPA.
anomaly_series

A technique for detecting anomalous segments based on CAPA.
ac_corrected

Transforms the data X to account for autocorrelation.
period_average

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

Detection of multivariate anomalous segments using PASS.
plot

Visualisation of data, collective and point anomalies.
collective_anomalies

Collective anomaly location, lags, and mean/variance changes.
capa.uv

Detection of univariate anomalous segments and points using CAPA.
robustscale

robustscale
point_anomalies

Point anomaly location and strength.
show

Displays S4 objects produced by capa methods.