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Malmgren, R.D., Stouffer, D.B., Motter, A.E. and Amaral, L.A.N. (2008) A Poissonian Explanation for Heavy Tails in E-Mail Communication. Proceedings of National Academy Science of USA, 105, 18153-18158.
http://dx.doi.org/10.1073/pnas.0800332105

has been cited by the following article:

  • TITLE: Heavy-Tailed Distributions Generated by Randomly Sampled Gaussian, Exponential and Power-Law Functions

    AUTHORS: Frederic von Wegner

    KEYWORDS: Heavy-Tailed Distributions, Random Sampling, Gaussian, Exponential, Power-Law

    JOURNAL NAME: Applied Mathematics, Vol.5 No.13, July 18, 2014

    ABSTRACT: A simple stochastic mechanism that produces exact and approximate power-law distributions is presented. The model considers radially symmetric Gaussian, exponential and power-law functions inn= 1, 2, 3 dimensions. Randomly sampling these functions with a radially uniform sampling scheme produces heavy-tailed distributions. For two-dimensional Gaussians and one-dimensional exponential functions, exact power-laws with exponent –1 are obtained. In other cases, densities with an approximate power-law behaviour close to the origin arise. These densities are analyzed using Padé approximants in order to show the approximate power-law behaviour. If the sampled function itself follows a power-law with exponent –α, random sampling leads to densities that also follow an exact power-law, with exponent -n/a – 1. The presented mechanism shows that power-laws can arise in generic situations different from previously considered specialized systems such as multi-particle systems close to phase transitions, dynamical systems at bifurcation points or systems displaying self-organized criticality. Thus, the presented mechanism may serve as an alternative hypothesis in system identification problems.