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research article

A characterization of the normal distribution using stationary max-stable processes

Engelke, Sebastian  
•
Kabluchko, Zakhar
2016
Extremes

Consider a max-stable process of the form , , where are points of the Poisson process with intensity u (-2)du on (0,a), X (i) , , are independent copies of a random d-variate vector X (that are independent of the Poisson process), and is a function. We show that the process eta is stationary if and only if X has multivariate normal distribution and kappa(t)-kappa(0) is the cumulant generating function of X. In this case, eta is a max-stable process introduced by R. L. Smith.

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Type
research article
DOI
10.1007/s10687-015-0235-z
Web of Science ID

WOS:000368999000001

Author(s)
Engelke, Sebastian  
Kabluchko, Zakhar
Date Issued

2016

Publisher

Springer Verlag

Published in
Extremes
Volume

19

Issue

1

Start page

1

End page

6

Subjects

Smith max-stable process

•

Stationarity

•

Extreme value theory

•

Multivariate normal distribution

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
STAT  
Available on Infoscience
April 1, 2016
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/125310
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