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Heavy-tailed time series / Rafal Kulik, Philippe Soulier.

9781071607374 (electronic book)
1071607375 (electronic book)
9781071607350

New York, NY : Springer, 2020.

English

1 online resource (677 pages).

10.1007/978-1-0716-0

QA273.6

519.2/4

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 chapters 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.

Includes bibliographical references and index.

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Description based on print version record.

Springer series in operations research.

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