Scaling detection in time series: diffusion entropy analysis.

  title={Scaling detection in time series: diffusion entropy analysis.},
  author={Nicola Scafetta and Paolo Grigolini},
  journal={Physical review. E, Statistical, nonlinear, and soft matter physics},
  volume={66 3 Pt 2A},
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. We 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). We… CONTINUE READING
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Publications referenced by this paper.
Showing 1-10 of 13 references

Statistical Physics II ͑Springer-Verlag

  • R Kubo, M Toda, N Hashitsume
  • Statistical Physics II ͑Springer-Verlag
  • 1991

Lectures on Phase Transitions and the Renormalization Group ͑Perseus

  • N Goldenfeld
  • Lectures on Phase Transitions and the…
  • 1985

LongTerm Storage: An Experimental Study ͑Constable

  • H E Hurst, R P Black, Y M Simaika
  • LongTerm Storage: An Experimental Study…
  • 1965

Limit Distributions for Sum of Independent Random Variables ͑Addison-Wesley

  • B V Gnedenko, A N Kolmogorov
  • Limit Distributions for Sum of Independent Random…
  • 1954

Mathematical Foundations of Statistical Mechanics ͑Dover Publications, Inc

  • A I Khinchin
  • Mathematical Foundations of Statistical Mechanics…
  • 1949

Phys. Rev. Lett

  • T Geisel, S Thomae
  • Phys. Rev. Lett
  • 1936


  • P Grigolini, L Palatella, G Raffaelli
  • Fractals


  • M F Shlesinger
  • Nature

Phys. Lett

  • N Scafetta, V Latora, P Grigolini
  • Phys. Lett

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