Modelling time series extremes

* 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. Key-Words: * Bayesian statistics; Box-Cox transformation;...

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Bibliographic Details
Published inRevstat Vol. 10; no. 1; p. 109
Main Authors Chavez-Demoulin, V, Davison, A.C
Format Journal Article
LanguageEnglish
Published Instituto Nacional de Estatistica 01.03.2012
Instituto Nacional de Estatística | Statistics Portugal
Subjects
Bayesian statistics
Box–Cox transformation
clustering
dependence
Distribution (Probability theory)
extremal index
extremogram
Mathematical research
Statistical models
Time-series analysis
Transformations (Mathematics)
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ISSN1645-6726
2183-0371
DOI10.57805/revstat.v10i1.113

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Summary:* 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. Key-Words: * 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. AMS Subject Classification: * 62E20, 62F15, 62G05, 62G08, 62G32, 62M05, 62M10.
ISSN:1645-6726
2183-0371
DOI:10.57805/revstat.v10i1.113