Heavy-tailed time series

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

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...

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Bibliographic Details
Main Author: Kulik, Rafal
Other Authors: Soulier, Philippe, Prof
Format: eBook
Language:English
Published: New York, NY : Springer, 2020.
Series:Springer series in operations research.
Subjects:
Extreme value theory.
Time-series analysis.
Probability & statistics.
Applied mathematics.
Mathematics > Probability & Statistics > General.
Mathematics > Applied.
Matemáticas > Estadística aplicada
Estadística aplicada
Extreme value theory
Time-series analysis
Online Access:Click for online access
Table of Contents:
  • 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.

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