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Weak Convergence and the Poisson Process

Chapter
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Part of the Springer Series in Operations Research and Financial Engineering book series (ORFE)

Abstract

This chapter exploits connections between regular variation and the Poisson process given in Theorems 6.2 (p. 179) and 6.3 (p. 180) to understand several limit theorems and also to understand how regular variation of distributions of random vectors is transmitted by various transformations on the vectors. The fundamental philosophy is that we should capitalize on the equivalence between the analytical concept of regular variation and the probabilistic notion of convergence of empirical measures to limiting Poisson random measures.

Keywords

Random Vector Weak Convergence Regular Variation Nonnegative Random Variable Extremal Process 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media, LLC 2007

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