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Crash Course II: Weak Convergence; Implications for Heavy-Tail Analysis

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

Abstract

Asymptotic properties of statistics in heavy-tailed analysis are clearly understood with an interpretation which comes from the modern theory of weak convergence of probability measures on metric spaces, as originally promoted in [22] and updated in [25]. Additionally, utilizing the power of weak convergence allows for a rather unified treatment of the one-dimensional and higher-dimensional cases of heavy-tailed phenomena.

Keywords

Weak Convergence Random Element Continuous Mapping Theorem Vague Topology Skorohod Topology 
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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