Parametric Statistical Change Point Analysis - Arjun K. Gupta

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Résumé :
This revised and expanded second edition is an in-depth study of the change point problem from a general point of view, as well as?a further examination of change point analysis of the most commonly used statistical models. Change point problems are encountered in such disciplines as economics, finance, medicine, psychology, signal processing, and geology, to mention only several. More?recently, change point analysis has been found?in extensive applications?related to?analyzing biomedical imaging data, array Comparative Genomic Hybridization (aCGH) data, and gene expression data.? The exposition throughout the work?is clear and systematic, with a great deal of introductory material included. Different models are presented in each chapter, including gamma and exponential models, rarely examined thus far in the literature.?Extensive examples throughout the text emphasize key concepts and different methodologies used, namely the likelihood ratio criterion as well as?the Bayesian and information criterion approaches. New examples of change point analysis in modern molecular biology and other fields?such as finance and air traffic control?are added in this second edition.?Also included are two new chapters on change points in the hazard function and other practical change point models such as the epidemic change point model and a smooth-and-abrupt change point model. An up-to-date comprehensive bibliography and two indices round out the work.

Biographie:
Qing Wang received the B.Eng. and Ph.D. degrees in control science and engineering from the School of Automation and Electrical Engineering, University of Science and Technology Beijing, Beijing, China, in 2013 and 2018, respectively. She is currently a lecturer at the School of Automation, Beijing Institute of Technology. Her current research interests include multi-agent systems, nonlinear systems, intelligent control, and distributed optimization. Bin Xin received the B.S. degree in information engineering and the Ph.D. degree in control science and engineering from the Beijing Institute of Technology, Beijing, China, in 2004 and 2012, respectively. He was an academic visitor at the Decision and Cognitive Sciences Research Centre at the University of Manchester from 2011 to 2012. He is currently a professor at the School of Automation, Beijing Institute of Technology. His current research interests include search and optimization, evolutionary computation, unmanned systems, and multi-agent systems. Jie Chen received the B.S., M.S., and Ph.D. degrees in control theory and control engineering from the Beijing Institute of Technology, Beijing, China, in 1986, 1996, and 2001, respectively. He was the President of Tongji University, Shanghai, China, during 2018-2023. He is a Professor with the Control Science and Engineering, Beijing Institute of Technology and Tongji University, where he serves as the Director of the National Key Laboratory of Autonomous Intelligent Unmanned Systems (KAIUS). He is the academician of the Chinese Academy of Engineering and the fellow of the IEEE and IFAC. His current research interests include complex systems, multiagent systems, multiobjective optimization and decision, and constrained nonlinear control....

Sommaire:

Preface.- Preliminaries.- Introduction.- Univariate Normal Model.- Multivariate Normal Model.- Regression Model.- Gamma Model.- Exponential Model.- Change Point Model for the Hazard Function.- Discrete Models.- Other Models.- Bibliography.- Author Index.- Subject Index.