Correlations of record events as a test for heavy-tailed distributions

J. Franke; G. Wergen; J. Krug

doi:10.1103/physrevlett.108.064101

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arXiv · 1109.2061

Correlations of record events as a test for heavy-tailed distributions

J. Franke·G. Wergen·J. Krug

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Abstract

A record is an entry in a time series that is larger or smaller than all previous entries. If the time series consists of independent, identically distributed random variables with a superimposed linear trend, record events are positively (negatively) correlated when the tail of the distribution is heavier (lighter) than exponential. Here we use these correlations to detect heavy-tailed behavior in small sets of independent random variables. The method consists of converting random subsets of the data into time series with a tunable linear drift and computing the resulting record correlations.

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BibTeX RIS

J. Franke, G. Wergen, J. Krug. 2012-01-06. Correlations of record events as a test for heavy-tailed distributions. https://doi.org/10.1103/physrevlett.108.064101

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