Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules
Author:   Alexander Tartakovsky (University of Connecticut, Storrs, USA)
Publisher:   Taylor & Francis Inc
ISBN:  

9781498757584


Pages:   320
Publication Date:   02 December 2019
Format:   Hardback
Availability:   In Print   Availability explained
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Sequential Change Detection and Hypothesis Testing: General Non-i.i.d. Stochastic Models and Asymptotically Optimal Rules


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Author:   Alexander Tartakovsky (University of Connecticut, Storrs, USA)
Publisher:   Taylor & Francis Inc
Imprint:   Chapman & Hall/CRC
Weight:   0.725kg
ISBN:  

9781498757584


ISBN 10:   1498757588
Pages:   320
Publication Date:   02 December 2019
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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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Author Information

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.

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