A Conditional Approach for Multivariate Extreme Values (with Discussion)

Lancaster University

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Abstract

Summary Multivariate extreme value theory and methods concern the characterization, estimation and extrapolation of the joint tail of the distribution of a d-dimensional random variable. Existing approaches are based on limiting arguments in which all components of the variable become large at the same rate. This limit approach is inappropriate when the extreme values of all the variables are unlikely to occur together or when interest is in regions of the support of the joint distribution where only a subset of components is extreme. In practice this restricts existing methods to applications where d is typically 2 or 3. Under an assumption about the asymptotic form of the joint distribution of a…

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Topics & keywords

Keywords
  • Extreme value theory
  • Joint probability distribution
  • Extrapolation
  • Econometrics
  • Marginal distribution
  • Conditional probability distribution
  • Tail dependence
  • Multivariate statistics
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