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Change Point Analysis for Time Series

Lajos Horváth, Gregory Rice
Livre relié | Anglais | Springer Statistics
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Description

This volume provides a comprehensive survey that covers various modern methods used for detecting and estimating change points in time series and their models. The book primarily focuses on asymptotic theory and practical applications of change point analysis. The methods discussed in the book go beyond the traditional change point methods for univariate and multivariate series. It also explores techniques for handling heteroscedastic series, high-dimensional series, and functional data. While the primary emphasis is on retrospective change point analysis, the book also presents sequential "on-line" methods for detecting change points in real-time scenarios. Each chapter in the book includes multiple data examples that illustrate the practical application of the developed results. These examples cover diverse fields such as economics, finance, environmental studies, and health data analysis. To reinforce the understanding of the material, each chapter concludes with several exercises.Additionally, the book provides a discussion of background literature, allowing readers to explore further resources for in-depth knowledge on specific topics. Overall, "Change Point Analysis for Time Series" offers a broad and informative overview of modern methods in change point analysis, making it a valuable resource for researchers, practitioners, and students interested in analyzing and modeling time series data.

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Parties prenantes

Auteur(s) :
Editeur:

Contenu

Nombre de pages :
545
Langue:
Anglais
Collection :

Caractéristiques

EAN:
9783031516085
Date de parution :
12-05-24
Format:
Livre relié
Format numérique:
Genaaid
Dimensions :
156 mm x 234 mm
Poids :
952 g

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