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

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

2011-09-09

arxiv.org/abs/1109.2061v2

Phys. Rev. Lett. 108, 064101 (2012)

Physics

Data Analysis, Statistics and Probability

Revised version, to appear in Physical Review Letters

Scientific paper

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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