Von Mises Conditions Revisited

Abstract

It is shown that the rate of convergence in the von Mises conditions of extreme value theory determines the distance of the underlying distribution function $F$ from a generalized Pareto distribution. The distance is measured in terms of the pertaining densities with the limit being ultimately attained if and only if $F$ is ultimately a generalized Pareto distribution. Consequently, the rate of convergence of the extremes in an iid sample, whether in terms of the distribution of the largest order statistics or of corresponding empirical truncated point processes, is determined by the rate of convergence in the von Mises condition. We prove that the converse is also true.