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Samples with a limit shape, multivariate extremes, and risk
by
Balkema, Guus
, Nolde, Natalia
in
Approximation
/ Continuity (mathematics)
/ Convergence
/ Mathematical analysis
/ Multivariate analysis
/ Normal distribution
/ Original Article
/ Original Articles
/ Probability
/ Probability distribution
/ Quantiles
/ Random variables
2020
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Samples with a limit shape, multivariate extremes, and risk
by
Balkema, Guus
, Nolde, Natalia
in
Approximation
/ Continuity (mathematics)
/ Convergence
/ Mathematical analysis
/ Multivariate analysis
/ Normal distribution
/ Original Article
/ Original Articles
/ Probability
/ Probability distribution
/ Quantiles
/ Random variables
2020
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Do you wish to request the book?
Samples with a limit shape, multivariate extremes, and risk
by
Balkema, Guus
, Nolde, Natalia
in
Approximation
/ Continuity (mathematics)
/ Convergence
/ Mathematical analysis
/ Multivariate analysis
/ Normal distribution
/ Original Article
/ Original Articles
/ Probability
/ Probability distribution
/ Quantiles
/ Random variables
2020
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Samples with a limit shape, multivariate extremes, and risk
Journal Article
Samples with a limit shape, multivariate extremes, and risk
2020
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Overview
Large samples from a light-tailed distribution often have a well-defined shape. This paper examines the implications of the assumption that there is a limit shape. We show that the limit shape determines the upper quantiles for a large class of random variables. These variables may be described loosely as continuous homogeneous functionals of the underlying random vector. They play an important role in evaluating risk in a multivariate setting. The paper also looks at various coefficients of tail dependence and at the distribution of the scaled sample points for large samples. The paper assumes convergence in probability rather than almost sure convergence. This results in an elegant theory. In particular, there is a simple characterization of domains of attraction.
Publisher
Cambridge University Press,Applied Probability Trust
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