New Estimators for the Extremal Index and Other Cluster Characteristics

Laurini, Fabrizio; Tawn, Jonathan A.

doi:10.1023/b:extr.0000031179.49454.90

Cited by 34 publications

(25 citation statements)

References 23 publications

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“…Smith and Weissman (1996) gave a review of estimators of the extremal index and proposed two estimating methods, i.e., blocks method and runs method. Other references include Chapter 8 in Embrechts et al (1997), Ferro and Segers (2003), and Laurini and Tawn (2003).…”

Section: The Extremal Indexmentioning

confidence: 99%

Asymptotically (in)dependent multivariate maxima of moving maxima processes

2007

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Smith and Weissman introduced a M4 class of processes which are very flexible models for temporally dependent multivariate extreme value processes. However all variables in these M4 models are asymptotically dependent and what this paper does is to extend this M4 class in a number of ways to produce classes of models which are also asymptotically independent. We shall study properties of the proposed models. In particular, asymptotic dependence indexes, coefficients of tail dependence, and extremal indexes are derived for each case.

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Section: The Extremal Indexmentioning

confidence: 99%

Asymptotically (in)dependent multivariate maxima of moving maxima processes

2007

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“…A pathbreaking paper for random recurrence models has been De Haan et al (1989). We refer in particular to Laurini and Tawn (2003) for recent results on the extremal index and further references, in particular, with respect to statistical estimation.…”

Section: Introductionmentioning

confidence: 99%

High-level dependence in time series models

2009

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We present several notions of high-level dependence for stochastic processes, which have appeared in the literature. We calculate such measures for discrete and continuous-time models, where we concentrate on time series with heavy-tailed marginals, where extremes are likely to occur in clusters. Such models include linear models and solutions to random recurrence equations; in particular, discrete and continuous-time moving average and (G)ARCH processes. To illustrate our results we present a small simulation study.

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“…We defined clusters as aggregates of consecutive days exceeding a threshold and kept the maximum in each formed cluster. The size of the clusters is an interesting feature of extremes [Laurini and Tawn, 2003], but it will not be investigated here.…”

Section: Methodsmentioning

confidence: 99%

Amplitude and frequency of temperature extremes over the North Atlantic region

Nogaj

Yiou

Parey

et al. 2006

Geophysical Research Letters

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[1] Recent studies on extreme events have focused on the potential change of their intensity during the 20th century, but their frequency evolution has often been overlooked although its socio-economic impact is equally important. This paper focuses on extreme events of high and low temperatures and their amplitude and frequency changes over the last 60 years in the North Atlantic (NA) region. We analyze the temporal evolution of the amplitude and frequency of extreme events through the parameters of an extreme value distribution applied to NCEP reanalysis for the winter and summer seasons. We examine the relation of the statistics of extremes with greenhouse gas forcing and an atmospheric circulation index and obtain a spatial distribution of the trends of those extreme parameters. We find that the frequency of warm extremes increases over most of the NA while their magnitude does not vary as systematically. Apart from the Labrador Sea and parts of Scandinavia, the features of winter cold extremes exhibit decreasing or no trends.

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New Estimators for the Extremal Index and Other Cluster Characteristics

Cited by 34 publications

References 23 publications

Asymptotically (in)dependent multivariate maxima of moving maxima processes

Asymptotically (in)dependent multivariate maxima of moving maxima processes

High-level dependence in time series models

Amplitude and frequency of temperature extremes over the North Atlantic region

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