Engelke, SebastianKabluchko, Zakhar2016-04-012016-04-012016-04-01201610.1007/s10687-015-0235-zhttps://infoscience.epfl.ch/handle/20.500.14299/125310WOS:000368999000001Consider 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.Smith max-stable processStationarityExtreme value theoryMultivariate normal distributiontext::journal::journal article::research article