Temporal scaling theory for bursty time series with clusters of arbitrarily many events

TL;DR

This paper introduces a model for bursty time series with correlated interevent times and burst sizes, deriving analytical relations for autocorrelation decay, which enhances understanding of long-term temporal correlations in complex systems.

Contribution

It provides the first analytical derivation of the autocorrelation function for time series with arbitrarily correlated interevent times and burst sizes, especially under power-law distributions.

Findings

Derived scaling relations between ACF decay and IET/burst size distributions.

Confirmed analytical results with numerical simulations.

Enhanced understanding of correlations' effects on long-term temporal behavior.

Abstract

Long-term temporal correlations in time series in a form of an event sequence have been characterized using an autocorrelation function (ACF) that often shows a power-law decaying behavior. Such scaling behavior has been mainly accounted for by the heavy-tailed distribution of interevent times (IETs), i.e., the time interval between two consecutive events. Yet little is known about how correlations between consecutive IETs systematically affect the decaying behavior of the ACF. Empirical distributions of the burst size, which is the number of events in a cluster of events occurring in a short time window, often show heavy tails, implying that arbitrarily many consecutive IETs may be correlated with each other. In the present study, we propose a model for generating a time series with arbitrary functional forms of IET and burst size distributions. Then, we analytically derive the ACF for the model time series. In particular, by assuming that the IET and burst size are power-law distributed, we derive scaling relations between power-law exponents of the ACF decay, IET distribution, and burst size distribution. These analytical results are confirmed by numerical simulations. Our approach helps to rigorously and analytically understand the effects of correlations between arbitrarily many consecutive IETs on the decaying behavior of the ACF.