Probability flux as a method for detecting scaling

Description:

Paper on probability flux as a method for detecting scaling.

Creator(s):
Creation Date: April 5, 2010
Partner(s):
UNT College of Arts and Sciences
Collection(s):
UNT Scholarly Works
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Creator (Author):
Ignaccolo, Massimiliano

Duke University

Creator (Author):
Grigolini, Paolo

University of North Texas

Creator (Author):
West, Bruce J.

United States. Army Research Office

Date(s):
  • Creation: April 5, 2010
Description:

Paper on probability flux as a method for detecting scaling.

Degree:
Department: Physics
Note:

This is the pre-print version of the paper.

Note:

Abstract: We introduce a new method for detecting scaling in time series. The method uses the properties of the probability flux for stochastic self-affine processes and is called the 'probability flux analysis' (PFA). The advantages of this method are: 1) it is independent of the finiteness of the moments of the self-affine process; 2) it does not require a binning procedure for numerical evaluation of the probability density function. These properties make the method particularly efficient for heavy tailed distributions in which the variance is not finite, for example, in Lévy α-stable processes. This utility is established using a comparison with the 'diffusion entropy' (DE) method.

Physical Description:

19 p.

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Subject(s):
Keyword(s): complex networks | probability flux analysis | diffusion entropy
Source: arXiv: 1004.0372
Partner:
UNT College of Arts and Sciences
Collection:
UNT Scholarly Works
Identifier:
  • ARK: ark:/67531/metadc132978
Resource Type: Paper
Format: Text
Rights:
Access: Public