Anomaly Detection in Streaming Nonstationary Temporal Data

Priyanga Dilini Talagala; Rob J Hyndman; Kate Smith-Miles; Sevvandi Kandanaarachchi; Mario A Munoz

Journal article

Anomaly Detection in Streaming Nonstationary Temporal Data

Priyanga Dilini Talagala, Rob J Hyndman, Kate Smith-Miles, Sevvandi Kandanaarachchi, Mario A Munoz

Journal of Computational and Graphical Statistics | AMER STATISTICAL ASSOC | Published : 2019

DOI: 10.1080/10618600.2019.1617160

University of Melbourne Researchers

Andres Munoz Acosta Author Mathematics and Statistics

Kate Smith-Miles Author Mathematics and Statistics

Related Projects (1)

Intruder Alert! Detecting And Classifying Events In Noisy Time Series

This project aims to address the mathematical challenges in automated early detection and classification of intrusion events in noisy time s..

Grants

Awarded by Australian Research Council through the Linkage Project

Funding Acknowledgements

This research was supported in part by the Monash eResearch Centre and eSolutions-Research Support Services through the use of the MonARCH (Monash Advanced Research Computing Hybrid) HPC Cluster. Funding was provided by the Australian Research Council through the Linkage Project LP160101885.