Point process models for novelty detection on spatial point patterns and their extremes

DOI10.1016/j.csda.2018.03.019zbMath1469.62112OpenAlexW2796835230WikidataQ130015912 ScholiaQ130015912MaRDI QIDQ1662930

Stijn E. Luca, Marco A. F. Pimentel, Peter J. Watkinson, David A. Clifton

Publication date: 20 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2018.03.019

zbMATH Keywords

point processesextreme value theoryone-class classificationnovelty detectionprocess monitoring

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Applications of statistics in engineering and industry; control charts (62P30) Extreme value theory; extremal stochastic processes (60G70) Statistics of extreme values; tail inference (62G32) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Related Items (1)

Anomaly Detection in Streaming Nonstationary Temporal Data

Uses Software

• Matlab
• R
• LIBRA
• astsa
• ismev
• LOF
• PRMLT

Cites Work

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• Estimating the Support of a High-Dimensional Distribution
• Determinantal Point Processes for Machine Learning
• Laws of Small Numbers: Extremes and Rare Events
• Handbook of Spatial Statistics
• An Introduction to the Theory of Point Processes
• Bayesian Reasoning and Machine Learning
• Data Mining and Knowledge Discovery Handbook
• An introduction to statistical modeling of extreme values

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