Time series of extremes

Brian J. Reich, Benjamin Adam Shaby

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations


Data collected for the purpose of an extreme value analysis very often exhibit temporal dependence. Examples include daily time series of stock prices, temperature, or water levels. In this chapter, we address two fundamental inferential objectives: estimating extreme marginal quantiles while accounting for serial dependence, and estimating the strength of serial dependence in extreme values. We review the literature for methods aimed at each of these objectives, including a survey of computational methods used for each approach. We illustrate the methods using an analysis of hourly wind gust speeds. R code to implement the methods is available online.

Original languageEnglish (US)
Title of host publicationExtreme Value Modeling and Risk Analysis
Subtitle of host publicationMethods and Applications
PublisherCRC Press
Number of pages22
ISBN (Electronic)9781498701310
ISBN (Print)9781498701297
StatePublished - Jan 6 2016

All Science Journal Classification (ASJC) codes

  • Mathematics(all)


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