Correlations of record events as a test for heavy-tailed distributions
Data Analysis, Statistics and Probability
2015-05-30 v2 Statistical Mechanics
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.
Keywords
Cite
@article{arxiv.1109.2061,
title = {Correlations of record events as a test for heavy-tailed distributions},
author = {J. Franke and G. Wergen and J. Krug},
journal= {arXiv preprint arXiv:1109.2061},
year = {2015}
}
Comments
Revised version, to appear in Physical Review Letters