Point processes, regular variation and weak convergence 论文

1986Advances in Applied Probability引用 299
Mathematical Approximation and IntegrationPoint processes and geometric inequalitiesBayesian Methods and Mixture Models

摘要

A method is reviewed for proving weak convergence in a function-space setting when regular variation is a sufficient condition. Point processes and weak convergence techniques involving continuity arguments play a central role. The method is dimensionless and holds computations to a minimum. Many applications of the methods to processes derived from sums and maxima are given.

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