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anomaly (version 4.3.3)

Detecting Anomalies in Data

Description

Implements Collective And Point Anomaly (CAPA) Fisch, Eckley, and Fearnhead (2022) , Multi-Variate Collective And Point Anomaly (MVCAPA) Fisch, Eckley, and Fearnhead (2021) , Proportion Adaptive Segment Selection (PASS) Jeng, Cai, and Li (2012) , and Bayesian Abnormal Region Detector (BARD) Bardwell and Fearnhead (2015) . These methods are for the detection of anomalies in time series data. Further information regarding the use of this package along with detailed examples can be found in Fisch, Grose, Eckley, Fearnhead, and Bardwell (2024) .

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Version

Install

install.packages('anomaly')

Monthly Downloads

402

Version

4.3.3

License

GPL

Maintainer

Daniel Grose

Last Published

August 19th, 2024

Functions in anomaly (4.3.3)

sim.data

Simulated data.
collective_anomalies

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

Displays S4 objects produced by capa methods.
sampler

Post processing of BARD results.
summary

Summary of collective and point anomalies.
plot

Visualisation of data, collective and point anomalies.
point_anomalies

Point anomaly location and strength.
machinetemp

Machine temperature data.
capa

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

Detection of multivariate anomalous segments using PASS.
anomaly-package

Detecting Anomalies in Data
bard

Detection of multivariate anomalous segments using BARD.