Publication

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

Sebastian Engelke
2016
Journal Articles

Abstract

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.

Official source

Graph Chat

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.

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

Chat with Graph Search

Extensions of Peer Prediction Incentive Mechanisms

Instabilities in Elastic and Magneto-Elastic Beams and Shells: from Shell Buckling to the Design of a Programmable Braille Reader

Generalization of Scaled Deep ResNets in the Mean-Field Regime