2.7k citations · 2.8k across the 32 of their papers we have counts for
6 papers · 1 filter
anomaly : Detection of Anomalous Structure in Time Series Data
Alex Fisch, Daniel Grose, Idris A. Eckley +2
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 seri…
Scalable changepoint and anomaly detection in cross-correlated data with an application to condition monitoring
Martin Tveten, Idris A. Eckley, Paul Fearnhead
Motivated by a condition monitoring application arising from subsea engineering we derive a novel, scalable approach to detecting anomalous mean structure in a subset of correlated…
Real Time Anomaly Detection And Categorisation
Alexander T. M. Fisch, Lawrence Bardwell, Idris A. Eckley
The ability to quickly and accurately detect anomalous structure within data sequences is an inference challenge of growing importance. This work extends recently proposed post-hoc…
Innovative And Additive Outlier Robust Kalman Filtering With A Robust Particle Filter
Alexander T. M. Fisch, Idris A. Eckley, P. Fearnhead
In this paper, we propose CE-BASS, a particle mixture Kalman filter which is robust to both innovative and additive outliers, and able to fully capture multi-modality in the distri…
The Local Partial Autocorrelation Function and Some Applications
Rebecca Killick, Marina I. Knight, Guy P. Nason +1
The classical regular and partial autocorrelation functions are powerful tools for stationary time series modelling and analysis. However, it is increasingly recognized that many t…
A novel change point approach for the detection of gas emission sources using remotely contained concentration data
Idris Eckley, Claudia Kirch, Silke Weber
Motivated by an example from remote sensing of gas emission sources, we derive two novel change point procedures for multivariate time series where, in contrast to classical change…