Learn R Programming

⚠️There's a newer version (4.3.3) of this package.Take me there.

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.

Copy Link

Version

Install

install.packages('anomaly')

Monthly Downloads

402

Version

4.0.2

License

GPL

Maintainer

Daniel Grose

Last Published

October 20th, 2021

Functions in anomaly (4.0.2)

moving_ac_corrected

Transforms the data X to account for autocorrelation using a moving window and a burn-in.

Detection of multivariate anomalous segments using BARD.

Kepler Lightcurve data.

Detection of multivariate anomalous segments using PASS.

Transforms the data X to account for autocorrelation.

Detection of multivariate anomalous segments and points using MVCAPA.

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

Detection of univariate anomalous segments using SCAPA.

Detection of univariate anomalous segments and points using CAPA.

Machine temperature data.

A function for generating simulated multivariate data

Summary of collective and point anomalies.

Displays S4 objects produced by capa methods.

Post processing of BARD results.

Online detection of multivariate anomalous segments and points using SMVCAPA.

plot-bard.sampler.class

Visualisation of data, collective and point anomalies.

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

collective_anomalies

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

point_anomalies

Point anomaly location and strength.