Description

Book Synopsis

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.



Trade Review

"The objective of this book is to present theoretical and numerical results for detection and estimation of changes in complex systems. Retrospective and sequential detection of the change-points is considered. …
I think that the book will be useful to many people because it presents the two types of change-point problems (retrospective and sequential), in various situations, presenting the theoretical results, simulations and real-world applications."
—Gabriela Ciuperca, in Mathematical Reviews Clippings, December 2017



Table of Contents

I Retrospective Problems

1 Preliminary considerations

2 General Retrospective Disorder Problem

3 Retrospective Detection and Estimation of Stochastic Trends

4 Retrospective Detection and Estimation of Switches in Univariate Models

5 Retrospective change-point detection and estimation in multivariate stochastic models

6 Retrospective Detection of Change-Points in State-Space Models

7 Copula, GARCH, and Other Financial Models

II Sequential Problems

8 Sequential hypothesis testing

9 Sequential change-point detection for univariate models

10 Sequential Change-Point Detection in Multivariate Models

11 Early change-point detection

12 Sequential Detection of Switches in Models with Changing Structures

13 Sequential detection and estimation of change-points

Bibliography

Index

ChangePoint Analysis in Nonstationary Stochastic

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    A Hardback by Boris Brodsky

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      Publisher: Taylor & Francis Inc
      Publication Date: Publication Date: 23/03/2017
      ISBN13: 9781498755962, 978-1498755962
      ISBN10: 1498755968

      Description

      Book Synopsis

      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.



      Trade Review

      "The objective of this book is to present theoretical and numerical results for detection and estimation of changes in complex systems. Retrospective and sequential detection of the change-points is considered. …
      I think that the book will be useful to many people because it presents the two types of change-point problems (retrospective and sequential), in various situations, presenting the theoretical results, simulations and real-world applications."
      —Gabriela Ciuperca, in Mathematical Reviews Clippings, December 2017



      Table of Contents

      I Retrospective Problems

      1 Preliminary considerations

      2 General Retrospective Disorder Problem

      3 Retrospective Detection and Estimation of Stochastic Trends

      4 Retrospective Detection and Estimation of Switches in Univariate Models

      5 Retrospective change-point detection and estimation in multivariate stochastic models

      6 Retrospective Detection of Change-Points in State-Space Models

      7 Copula, GARCH, and Other Financial Models

      II Sequential Problems

      8 Sequential hypothesis testing

      9 Sequential change-point detection for univariate models

      10 Sequential Change-Point Detection in Multivariate Models

      11 Early change-point detection

      12 Sequential Detection of Switches in Models with Changing Structures

      13 Sequential detection and estimation of change-points

      Bibliography

      Index

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