title: Correlations of record events as a test for heavy-tailed distributions.
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.
authors.affiliation: Institute of Theoretical Physics, University of Cologne, Köln, Germany.
authors.forename: J
authors.initials: J
authors.lastname: Franke
authors.forename: G
authors.initials: G
authors.lastname: Wergen
authors.forename: J
authors.initials: J
authors.lastname: Krug