Abstract

Records among a sequence of iid random variables X1,X2,…X_1,X_2,\dotsc on the real line have been investigated extensively over the past decades. A record is defined as a random variable XnX_n such that Xn>max⁡(X1,…,Xn−1)X_n>\max(X_1,\dotsc,X_{n-1}). Trying to generalize this concept to the case of random vectors, or even stochastic processes with continuous sample paths, the question arises how to define records in higher dimensions. We introduce two different concepts: A simple record is meant to be a stochastic process (or a random vector) XnX_n that is larger than X1,…,Xn−1 X_1,\dotsc, X_{n-1} in at least one component, whereas a complete record has to be larger than its predecessors in all components. The behavior of records is investigated. In particular, the probability that a stochastic process Xn X_n is a record as nn tends to infinity is studied, assuming that the processes are in the max-domain of attraction of a max-stable process. Furthermore, the distribution of Xn X_n, given that Xn X_n is a record is derived.

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