Heavy-Tailed Time Series (Springer Series in Operations Research and Financial Engineering) - Hardcover

Buch 38 von 43: Springer Series in Operations Research and Financial Engineering

Kulik, Rafal; Soulier, Philippe

 
9781071607350: Heavy-Tailed Time Series (Springer Series in Operations Research and Financial Engineering)

Inhaltsangabe

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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Über die Autorin bzw. den Autor

Rafal Kulik graduated from the University of Wroclaw, Poland. He is currently a Professor at the Department of Mathematics and Statistics, University of Ottawa. His research interests are centered around limit theorems for stochastic  processes with temporal dependence. 

Philippe Soulier graduated from Ecole Normale Supérieure de Paris and obtained his PhD at University Paris XI Orsay. He is Professor of Mathematics at University Paris Nanterre. His main themes of research are long memory processes and extreme value theory.

Von der hinteren Coverseite

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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9781071607367: Heavy-Tailed Time Series

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ISBN 10:  1071607367 ISBN 13:  9781071607367
Verlag: Springer, 2020
Softcover