Heavy-Tailed Time Series

Rafal Kulik, Philippe Soulier (Autoren)

Buch | Hardcover

681 Seiten

2020 | 1st ed. 2020
Springer-Verlag New York Inc.
978-1-0716-0735-0 (ISBN)

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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.

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.

Regular variation.- Regularly varying random variables.- Regularly varying random vectors.- Dealing with extremal independence.- Regular variation of series and random sums.- Regularly varying time series.- Limit theorems.- Convergence of clusters-. Point process convergence.- Convergence to stable and extremal processes.- The tall empirical and quantile processes.- Estimation of cluster functionals.- Estimation for extremally independent time series.- Bootstrap.- Time series models.- Max-stable processes.- Markov chains.- Moving averages.- Long memory processes.- Appendices.

Erscheinungsdatum	10.07.2020
Reihe/Serie	Springer Series in Operations Research and Financial Engineering
Zusatzinfo	5 Illustrations, color; 2 Illustrations, black and white; XIX, 681 p. 7 illus., 5 illus. in color.
Verlagsort	New York, NY
Sprache	englisch
Maße	155 x 235 mm
Themenwelt	Mathematik / Informatik ► Mathematik ► Angewandte Mathematik
Themenwelt	Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
Schlagworte	extremal processes • extreme value theory • point processes • stable processes • Statistics of extreme values • tail inference • Time Series
ISBN-10	1-0716-0735-9 / 1071607359
ISBN-13	978-1-0716-0735-0 / 9781071607350
Zustand	Neuware