Return intervals of rare events in records with long-term persistence

Armin Bunde, Jan F. Eichner, Shlomo Havlin and Jan W. Kantelhardt

Physica A: Statistical Mechanics and its Applications, 2004, vol. 342, issue 1, 308-314

Abstract: Many natural records exhibit long-term correlations characterized by a power-law decay of the auto-correlation function, C(s)∼s−γ, with time lag s and correlation exponent 0<γ<1. We study, how the presence of such correlations affects the statistics of the return intervals rq for events above a certain threshold value q. We find that (a) the mean return interval Rq does not depend on γ, (b) the distribution of rq follows a stretched exponential, lnPq(r)∼−(r/Rq)γ, and (c) the return intervals are also long-term correlated with the exponent γ, yielding clustering of both small and large return intervals. We provide indications that both the stretched exponential behaviour and the clustering of rare events can be seen in long temperature records.

Keywords: Long-term correlations; Time series; Rare events; Return periods; Clustering; Temperature records (search for similar items in EconPapers)
Date: 2004
References: View complete reference list from CitEc
Citations: View citations in EconPapers (9)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S037843710400487X
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:342:y:2004:i:1:p:308-314

DOI: 10.1016/j.physa.2004.01.069

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().