Detection and Diagnosis of Unknown Abrupt Changes Using CUSUM Multi-Chart Schemes

DOI10.1080/07474940701404765zbMath1116.62081OpenAlexW1996146454MaRDI QIDQ5297917

Dong Han, Fugee Tsung

Publication date: 16 July 2007

Published in: Sequential Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/07474940701404765

zbMATH Keywords

asymptotic optimalitysequential analysisKullback-Leibler information distancesonline detection and diagnosis

Mathematics Subject Classification ID

Applications of statistics in engineering and industry; control charts (62P30) Monte Carlo methods (65C05) Sequential statistical analysis (62L10)

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The optimized CUSUM and EWMA multi-charts for jointly detecting a range of mean and variance change ⋮ Multichart schemes for detecting changes in disease incidence ⋮ Detection of changes in a random financial sequence with a stable distribution ⋮ CUSUM multi-chart for detecting unknown abrupt changes under finite measure space for network observation sequences ⋮ CUSUM multi-chart based on nonparametric likelihood approach for detecting unknown abrupt changes and its application for network data ⋮ Asymptotic optimized CUSUM and EWMA multi-charts for jointly detecting and diagnosing unknown change ⋮ Optimal Sequential Surveillance for Finance, Public Health, and Other Areas ⋮ Detection and Diagnosis of Distribution Changes of Degree Ratio in Complex Networks

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