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Publications & Journals

anomaly : Detection of Anomalous Structure in Time Series Data

Citation:

Fisch, A., Grose, D., Eckley, i., Fearnhead, P., Bardwell, L., (2020) anomaly: Detection of Anomalous Structure in Time Series Data. arXiv:2010.09353

Published:

19/10/2020

Link:

University:

University of Lancaster

Abstract: 

One of the contemporary challenges in anomaly detection is the ability to detect, and differentiate between, both point and collective anomalies within a data sequence or time series. The \pkg{anomaly} package has been developed to provide users with a choice of anomaly detection methods and, in particular, provides an implementation of the recently proposed CAPA family of anomaly detection algorithms. This article describes the methods implemented whilst also highlighting their application to simulated data as well as real data examples contained in the package.

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