Alexander Tartakovsky

Sequential Change Detection and Hypothesis Testing (eBook, PDF)

General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules

• Format: PDF

Produktbeschreibung

This book presents an overview of methodology in these related areas, providing a synthesis of research from the last few decades. The methods are illustrated through real data examples, and software is referenced where possible. The emphasis is on providing all the theoretical details in a unified framework.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 300
• Erscheinungstermin: 11. Dezember 2019
• Englisch
• ISBN-13: 9781498757591
• Artikelnr.: 58397834

Autorenporträt

Alexander Tartakovsky is a Professor and Head of the Space Informatics Laboratory at the Moscow Institute of Physics and Technology and President of AGT StatConsult, Los Angeles, California, USA. From 1997 to 2013, he was a Professor at the Department of Mathematics and the Associate Director of the Center for Applied Mathematical Sciences at the University of Southern California, Los Angeles. From 2013 to 2015, he was a Professor at the Department of Statistics at the University of Connecticut at Storrs. He is a fellow of the Institute of Mathematical Statistics and a recipient of the 2007 Abraham Wald Award in Sequential Analysis. His research interests include theoretical and applied statistics, sequential analysis, changepoint detection phenomena, statistical image and signal processing, video surveillance and object detection and tracking, information integration/fusion, cybersecurity, and detection and tracking of malicious activity. He is the author of three books, several book chapters, and over 150 journal and conference publications.

Inhaltsangabe

1 Introduction and Motivation
2 Elements of optimal stopping theory
3 Changepoint models
4 Bayesian approaches
5 The Lorden criterion
6 Alternative versions of the Lorden criterion
7 CUSUM for Poisson processes
8 The maximal probability criterion
9 The Pollak criterion
10 Finite time horizon problems
11 Two-sided problems
12 Quickest detection of changes with composite hypotheses
13 Quickest change detection in multiple sensors/populations
14 Performance evaluation
15 Retrospective change detection
16 Sequential hypothesis testing
17 Sequential tests of composite hypotheses
18 Sequential hypothesis testing in multiple sensors/populations
19 Sequential Estimation
20 Applications and Extensions.

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1 Introduction and Motivation; 2 Elements of optimal stopping theory; 3 Changepoint models; 4 Bayesian approaches; 5 The Lorden criterion; 6 Alternative versions of the Lorden criterion; 7 CUSUM for Poisson processes; 8 The maximal probability criterion; 9 The Pollak criterion; 10 Finite time horizon problems;11 Two-sided problems; 12 Quickest detection of changes with composite hypotheses; 13 Quickest change detection in multiple sensors/populations; 14 Performance evaluation; 15 Retrospective change detection; 16 Sequential hypothesis testing; 17 Sequential tests of composite hypotheses; 18 Sequential hypothesis testing in multiple sensors/populations; 19 Sequential Estimation; 20 Applications and Extensions.