Synopsis
This work is an in-depth study of the change point problem from a general point of view and 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. The exposition 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. Other models covered in detail are the multivariate normal, univariate normal, regression, and discrete models. Extensive examples throughout the text emphasize key concepts and different methodologies are used, namely the likelihood ratio criterion, and the Bayesian and information criterion approaches. A comprehensive bibliography and two indices complete the study.
About the Author
JIE CHEN, PhD, is Professor of Electrical Engineering at the University of California, Riverside. GUOXIANG GU, PhD, is Professor in the Department of Electrical and Computer Engineering at Louisiana State University, Baton Rouge.
"About this title" may belong to another edition of this title.