Modelling Time Series Extremes

V. Chavez-Demoulin; A.C. Davison

doi:10.57805/revstat.v10i1.113

Modelling Time Series Extremes

Authors

V. Chavez-Demoulin University of Lausanne
A.C. Davison Ecole Polytechnique Fédérale de Lausanne

DOI:

https://doi.org/10.57805/revstat.v10i1.113

Keywords:

Bayesian statistics, Box–Cox transformation, clustering, dependence, extremal index, extremogram, generalized extreme-value distribution, generalized Pareto distribution, Hill estimator, nonparametric smoothing, non-stationarity, regression, tail index

Abstract

The need to model rare events of univariate time series has led to many recent advances in theory and methods. In this paper, we review telegraphically the literature on extremes of dependent time series and list some remaining challenges.

Downloads

REVSTAT2012v10n1_5

Published

2012-04-05

How to Cite

Chavez-Demoulin , V., & Davison , A. (2012). Modelling Time Series Extremes. REVSTAT-Statistical Journal, 10(1), 109–133. https://doi.org/10.57805/revstat.v10i1.113