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Further reading

Culbreth, G., Baxley, J. and Lambert, D., 2023

Culbreth, G., Baxley, J. and Lambert, D., 2023. Detecting temporal scaling with modified diffusion entropy analysis. arXiv preprint arXiv:2311.11453

Culbreth, G., West, B.J. and Grigolini, P., 2019

Culbreth, G., West, B.J. and Grigolini, P., 2019. Entropic approach to the detection of crucial events. Entropy, 21(2), p.178. doi:10.3390/e21020178

Note

  • This paper introduced the stripes and describes their role with figure examples.
  • This paper used \(\eta\) to denote scaling, rather than \(\delta\).

Scafetta, N. and Grigolini, P., 2002

Scafetta, N. and Grigolini, P., 2002. Scaling detection in time series: Diffusion entropy analysis. Physical Review E, 66(3), p.036130. doi:10.1103/PhysRevE.66.036130

Note

The actual algorithm for DEA is detailed (mostly only in words) in Section IV.

Grigolini, P., Palatella, L. and Raffaelli, G., 2001

Grigolini, P., Palatella, L. and Raffaelli, G., 2001. Asymmetric anomalous diffusion: an efficient way to detect memory in time series. Fractals, 9(04), pp.439-449. doi:10.1142/S0218348X01000865

Note

This paper introduced always using positive steps when constructing the event array, rather than the sign of the step at that time index.