Alexander Tartakovsky, Igor Nikiforov, Michele Basseville

"The authors of this book are the leading researchers in the field of sequential analysis, and they have done a fantastic job in summarizing a comprehensive area. The book is well structured and is a useful reference text. The book contains over 500 references, and it is impressive that the authors have surveyed the field so well. For anyone working in sequential analysis, this book is a 'must-buy' and will probably become the seminal textbook in a short period of time." -Journal of the Royal Statistical Society, Series A, 2015 "... an impressive account of the current state of the art. It is fully up-to-date and builds on many recent scientific results. Furthermore, the authors seem to have strived for completeness and supply an overwhelming amount of information, provided in a systematic and comprehensible fashion. ... a highly valuable reference book for those working in the area of sequential analysis." -Journal of Applied Statistics, 2015 "This book is a significant leap forward in summarizing and unifying the contemporary approaches and results in the two important directions of sequential analysis: hypothesis testing and change-point detection. This will undoubtedly be the key reference for researchers, practitioners, and perhaps graduate students for the coming decades." -Dr. Michael Baron, Professor, Department of Mathematics and Statistics, American University "This book provides a timely consolidation of mathematics and applications relating to hypothesis testing and changepoint detection within sequential analysis. Make no mistake, this book is not suitable for those who have limited understanding of mathematical concepts. The authors have not shied away from including all the mathematical constructs from background knowledge to proofs of complex results. However, everything is conveyed in an easy to follow manner and the book includes a range of realistic examples that cover the complexities a researcher will encounter in real data. This book is set to become a key reference text for anyone working in this area." -Rebecca Killick, Lancaster University

• Motivations for the sequential approach. Background on probability and statistics. Sequential Hypothesis Testing: Sequential hypothesis testing-Two simple hypotheses. Sequential hypothesis testing-Multiple simple hypotheses. Sequential hypothesis testing-Composite hypotheses. Change-Point Detection: Statistical models with changes-Problem formulations and optimality criteria. Sequential change-point detection-Bayesian approach. Sequential change-point detection-Non-Bayesian approaches. Multichart change-point detection procedures for composite hypotheses and multipopulation models. Sequential change-point detection and isolation. Applications: Selected applications.