Non-extensive diffusion entropy analysis: non-stationarity in teen birth phenomena Metadata

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Title

  • Main Title Non-extensive diffusion entropy analysis: non-stationarity in teen birth phenomena

Creator

  • Author: Scafetta, Nicola
    Creator Type: Personal
    Creator Info: Duke University
  • Author: Grigolini, Paolo
    Creator Type: Personal
    Creator Info: University of North Texas; Università di Pisa
  • Author: Hamilton, P.
    Creator Type: Personal
    Creator Info: Texas Woman's University
  • Author: West, Bruce J.
    Creator Type: Personal
    Creator Info: Duke University; United States. Army Research Office

Date

  • Creation: 2008-02-06

Language

  • English

Description

  • Physical Description: 10 p.: ill.
  • Content Description: Paper discussing non-extensive diffusion entropy analysis and non-stationarity in teen birth phenomena.

Subject

  • Keyword: diffusion entropy analysis
  • Keyword: Tsallis
  • Keyword: q-entropy
  • Keyword: teen birth

Source

  • Website: arXiv: cond-mat/0205524

Collection

  • Name: UNT Scholarly Works
    Code: UNTSW

Institution

  • Name: UNT College of Arts and Sciences
    Code: UNTCAS

Rights

  • Rights Access: public

Resource Type

  • Paper

Format

  • Text

Identifier

  • Archival Resource Key: ark:/67531/metadc174685

Degree

  • Academic Department: Physics

Note

  • Display Note: This is the pre-print version of the paper.
  • Display Note: Abstract: A complex process is often a balance between non-stationary and stationary components. We show how the non-extensive Tsallis q-entropy indicator may be interpreted as a measure of non-stationarity in time series. This is done by applying the non-extensive entropy formalism to the Diffusion Entropy Analysis (DEA). We apply the analysis to the study of the teen birth phenomenon. We find that the unmarried teen births are strongly influenced by social processes with memory. This memory is related to the strength of the non-stationary component of the signal and is more intense than that in the married teen time series. By using the wavelet multiresolution analysis we attempt to give a social interpretation of this effect.
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