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Deformation of power law in the double Pareto distribution using uniformly distributed observation time

Published 14 Mar 2024 in cond-mat.stat-mech and math.PR | (2403.12091v2)

Abstract: The double Pareto distribution is a heavy-tailed distribution with a power-law tail, that is generated via geometric Brownian motion with an exponentially distributed observation time. In this study, we examine a modified model wherein the exponential distribution of the observation time is replaced with a continuous uniform distribution. The probability density, complementary cumulative distribution, and moments of this model are exactly calculated. Furthermore, the validity of the analytical calculations is discussed in comparison with numerical simulations of stochastic processes.

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References (26)
  1. van Kampen N G 1992 Stochastic Processes in Physics and Chemistry (Elsevier)
  2. Redner S 2001 A Guide to First-Passage Processes (Cambridge University Press)
  3. Nair J, Wierman A and Zwart B 2022 The Fundamentals of Heavy Tails (Cambridge University Press)
  4. Nishimori H and Ortiz G 2011 Elements of Phase Transitions and Critical Phenomena (Oxford University Press)
  5. ben-Avraham D and Havlin S 2000 Diffusion and Reaction in Fractals and Disordered Systems (Cambridge University Press)
  6. Zwanzig R 2001 Nonequilibrium Statistical Mechanics (Oxford University Press)
  7. Newman M E J 2005 Power laws, Pareto distributions and Zipf’s law Contemp. Phys. 46 323–351
  8. Limpert E, Stahel W A and Abbt M 2001 Log-normal distributions across the sciences: keys and clues BioScience 51 341–352
  9. Crow E L and Shimizu K (ed.) 1988 Lognormal distributions (Dekker)
  10. Uttley P, McHardy I M and Vaughan S 2005 Non-linear X-ray variability in X-ray binaries and active galaxies Mon. Not. R. Aston. Soc. 359 345–362
  11. Yamamoto K and Wakita J 2016 Analysis of a stochastic model for bacterial growth and the lognornality of the cell-size distribution J. Phys. Soc. Jpn. 85 074004
  12. Koyama K, Yamamoto K and Ushio M 2017 A lognormal distribution of the lengths of terminal twigs on self-similar branches of elm trees Proc. R. Soc. B 284 20162395
  13. Kolmogorov A N 1941 On the log-normal distribution of particles sizes during breakup process Dokl. Akad. Nauk SSSR 31 99–101
  14. Takayasu H, Sato A and Takayasu M 1997 Stable infinite variance fluctuations in randomly amplified Langevin systems Phys. Rev. Lett. 79 966–969
  15. Manrubia S C and Zanette D H 1999 Stochastic multiplicative processes with reset events Phys. Rev. E 59 4945–4948
  16. Yamamoto K and Yamazaki Y 2012 Power-law behavior in a cascade process with stopping events Phys. Rev. E 85 011145
  17. Yamamoto K 2014 Stochastic model of Zipf’s law and the universality of the power-law exponent Phys. Rev. E 89 042115
  18. Yamamoto K 2015 A simple view of the heavy-tailed sales distributions and application to the box-office grosses of U.S. movies Europhys. Lett. 108 68004
  19. Levy M and Solomon S 1996 Power laws are logarithmic Boltzmann laws Int. J. Mod. Phys. C 7 595–601
  20. Yamamoto K and Yamazaki Y 2022 Analysis and application of multiplicative stochastic process with a sample-dependent lower bound J. Phys. Soc. Jpn. 91 064803
  21. Øksendal B 2013 Stochastic Differential Equations (Springer)
  22. Paul W and Baschnagel J 2013 Stochastic Processes: From Physics to Finance (Springer)
  23. Reed W J and Jorgensen M 2004 The double Pareto-lognormal distribution—a new parametric model for size distributions Commn. Statist. 33 1733–1753
  24. Mitzenmacher M 2004 Dynamic models for file sizes and double Pareto distributions Internet Math. 1 305–333
  25. Reed W J 2001 The Pareto, Zipf and other power laws Econ. Lett. 74 15
  26. Grbac N and Grbac T G 2023 Letter to the editor: on the paper “The double Pareto-lognormal distribution—a new parametric model for size distributions” and its correction Commn. Statistics (DOI: 10.1080/03610926.2023.2174788)

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