Scaling Detection in Time Series: Diffusion Entropy Analysis

Description:

This article discusses scaling detection in time series.

Creator(s):
Creation Date: September 25, 2002
Partner(s):
UNT College of Arts and Sciences
Collection(s):
UNT Scholarly Works
Usage:
Total Uses: 125
Past 30 days: 4
Yesterday: 0
Creator (Author):
Scafetta, Nicola

Duke University; University of North Texas

Creator (Author):
Grigolini, Paolo

University of North Texas; Universitá di Pisa and INFM; Istituto di Biofisica CNR

Publisher Info:
Publisher Name: American Physical Society
Place of Publication: [College Park, Maryland]
Date(s):
  • Creation: September 25, 2002
Description:

This article discusses scaling detection in time series.

Degree:
Department: Physics
Note:

Copyright 2002 American Physical Society. The following article appeared in Physical Review E, 66:3; http://pre.aps.org/abstract/PRE/v66/i3/e036130

Note:

Abstract: The methods currently used to determine the scaling exponent of a complex dynamic process described by a time series are based on the numerical evaluation of variance. This means that all of them can be safely applied only to the case where ordinary statistical properties hold true even if strange kinetics are involved. The authors illustrate a method of statistical analysis based on the Shannon entropy of the diffusion process generated by the time series, called diffusion entropy analysis (DEA). The authors adopt artificial Gauss and Lévy time series, as prototypes of ordinary and anomalous statistics, respectively, and the authors analyze them with the DEA and four ordinary methods of analysis, some of which are very popular. The authors show that the DEA determines the correct scaling exponent even when the statistical properties, as well as the dynamic properties, are anomalous. The other four methods produce correct results in the Gauss case but fail to detect the correct scaling in the case of Lévy statistics.

Physical Description:

10 p.

Language(s):
Subject(s):
Keyword(s): scaling detection | diffusion entropy
Source: Physical Review E, 2002, College Park: American Physical Society
Partner:
UNT College of Arts and Sciences
Collection:
UNT Scholarly Works
Identifier:
  • DOI: 10.1103/PhysRevE.66.036130
  • ARK: ark:/67531/metadc67632
Resource Type: Article
Format: Text
Rights:
Access: Public
Citation:
Publication Title: Physical Review E
Volume: 66
Issue: 3
Pages: 10
Peer Reviewed: Yes