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Change-Point Analysis in Nonstationary Stochastic Models

Boris Brodsky
€63.99
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A01=Boris Brodsky
abrupt change
Asymptotically Optimal
Author_Boris Brodsky
Category=PBT
Change Point Detection
Change Point Detection Methods
Change Point Detection Problems
Change Point Estimates
Change Point Parameter
Change Point Problem
copula
Copula Models
Cramer's Condition
Cramer’s Condition
CUSUM Method
CUSUM Test
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
financial time series analysis
GARCH Model
hypothesis testing
Multiple Change Points
multivariate models
multivariate statistical modeling
Normalized Delay Time
optimal change-point detection techniques
Priori Inequality
retrospective detection
sequential analysis methods
Sequential Change Point Detection
Sequential Detection
sequential methods
Skorokhod Space
state-space estimation
statistical change detection
SV Model
time series segmentation
Unit Root
Unknown Change Point

Product details

  • ISBN 9781032402208
  • Weight: 517g
  • Dimensions: 156 x 234mm
  • Publication Date: 29 Aug 2022
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
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Description

This book covers the development of methods for detection and estimation of changes in complex systems. These systems are generally described by nonstationary stochastic models, which comprise both static and dynamic regimes, linear and nonlinear dynamics, and constant and time-variant structures of such systems. It covers both retrospective and sequential problems, particularly theoretical methods of optimal detection. Such methods are constructed and their characteristics are analyzed both theoretically and experimentally.

Suitable for researchers working in change-point analysis and stochastic modelling, the book includes theoretical details combined with computer simulations and practical applications. Its rigorous approach will be appreciated by those looking to delve into the details of the methods, as well as those looking to apply them.

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