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Heavy-Tailed Time Series

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Provides a comprehensive and self-contained overview of extreme value theory for time series Presents concise theoretical analysis of regular variation and weak convergence, with relation to time series Includes complete proofs and exercises with solutions Includes list of open problems to encourage future research?

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This book aims to present a comprehensive, self-contained, and concise overview of extreme value theory for time series, incorporating the latest research trends alongside classical methodology. Appropriate for graduate coursework or professional reference, the book requires a background in extreme value theory for i.i.d. data and basics of time series. Following a brief review of foundational concepts, it progresses linearly through topics in limit theorems and time series models while including historical insights at each chapter’s conclusion. Additionally, the book incorporates complete proofs and exercises with solutions as well as substantive reference lists and appendices, featuring a novel commentary on the theory of vague convergence.

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Book Format

Hardcover, Softcover

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Book information

Edition
1st Edition
ISBN [Hardcover]
9781071607350
Publisher
Springer
Year
2020
Pages
XIX, 681 p.
Series Title
Springer Series in Operations Research and Financial Engineering
Language
English
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