Haipeng Xing, Tze Leung Lai

Change-point Methodology and Applications

• Gebundenes Buch

Produktbeschreibung

This book presents an overview of the diverse literature on change-point methodology and describes some unifying themes and recent breakthroughs. It can be used as a second-year Ph.D. level course in statistics. It is expected to be useful to researchers and graduate students, not only in statistics but also in engineering, biomedicine, economics and finance.

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Produktdetails

• Verlag: Taylor & Francis Inc
• Seitenzahl: 300
• Erscheinungstermin: 15. Mai 2026
• Englisch
• Abmessung: 234mm x 156mm
• Gewicht: 453g
• ISBN-13: 9781466590137
• ISBN-10: 1466590130
• Artikelnr.: 63427450

Autorenporträt

Tze Leung Lai is affiliated with the Department of Statistics, Stanford University. Haipeng Xing is affiliated with the Department of Applied Mathematics and Statistics, SUNY Stony Brook. Both Lai and Xing are well-known statisticians and have made a number of important contributions in the subject of change-point problems (including both theory and applications).

Inhaltsangabe

Introduction. Statistical Quality Control and Fault Detection in Dynamical
Systems. Change-Point Models and Segmentation. Kalman and Wonham Filters.
Frequentist, Bayes and Empirical Bayes Approaches. Overview of Diverse
Fields of Application. Basic Change-Point Methodology. Sequential
Change-Point Detection. Page's Cusum Rule and Its Optimality Theory.
Bayesian Formulation and the Shiryaev-Robert's Rule. Asymptotically Optimal
Window-Limited Generalized Likelihood Ratio. Detection of Unknown Pre- and
Post-Parameter Changes. Implementation. Fixed-Sample Change-Point Problems.
Estimation and Testing of Single Change-Point. Likelihood and Bayesian
Approaches to Multiple Change-Points. Bic, Modified Bic and Other Model
Selection Criteria. Dynamic Programming and Segmentation. Bayesian Approach
and Mcmc Implementation. Sequential Monte Carlo Methods. an Empirical Bayes
Approach. Interplay Between Sequential and Fixed-Sample Problems. Alarm
Signaling Time and Scan Statistics. Filtering and Smoothing in Hidden
Markov Models. Multiple Change-Points and Sequential Surveillance.
Applications to Engineering. on-Line Fault Detection and Diagnosis. Signal
Detection and Target Tracking. Stochastic Control of Systems with
Occasional Unknown Parameter Changes. Applications to Biology and Medicine.
Analysis of Copy Number Variation (Cnv) Data. Circular Binary Segmentation.
Stochastic Segmentation Models. Analysis of Next Generation Sequencing
(Ngs) Data. Chip-Seq Data. Dna Methylation. Post-Marketing
Pharmacovigilance and Surveillance in Public Health. Applications to
Economics and Finance. Structural Changes in Econometric Time Series.
Change-Point Models in Finance.