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Extremal analysis of short series with out-liers: sea-levels and athletic records.

Research output: Contribution to journalJournal article

<mark>Journal publication date</mark>1999
<mark>Journal</mark>Journal of the Royal Statistical Society: Series C (Applied Statistics)
Issue number4
Number of pages19
Pages (from-to)469-487
Publication StatusPublished
<mark>Original language</mark>English


The analysis of extreme values is often required from short series which are biasedly sampled or contain outliers. Data for sea-levels at two UK east coast sites and data on athletics records for women's 3000 m track races are shown to exhibit such characteristics. Univariate extreme value methods provide a poor quantification of the extreme values for these data. By using bivariate extreme value methods we analyse jointly these data with related observations, from neighbouring coastal sites and 1500 m races respectively. We show that using bivariate methods provides substantial benefits, both in these applications and more generally with the amount of information gained being determined by the degree of dependence, the lengths and the amount of overlap of the two series, the homogeneity of the marginal characteristics of the variables and the presence and type of the outlier.