paper

Emergence of -statistical functions in a generalized binomial distribution with strong correlations

arXiv:1412.0006 · doi:10.1063/1.4919678

Abstract

We study a symmetric generalization of the binomial distribution recently introduced by Bergeron et al, where denotes the win probability, and is a positive parameter. This generalization is based on -exponential generating functions ( where . The numerical calculation of the probability distribution function of the number of wins , related to the number of realizations , strongly approaches a discrete -Gaussian distribution, for win-loss equiprobability (i.e., ) and all values of . Asymptotic distribution is in fact a -Gaussian , where and . The behavior of the scaled quantity is discussed as well. For , a large-deviation-like property showing a -exponential decay is found, where . For , and are related through , . For , the law of large numbers is violated, and we consistently study the large-deviations with respect to the probability of the limit distribution, yielding a power law, although not exactly a -exponential decay. All -statistical parameters which emerge are univocally defined by . Finally we discuss the analytical connection with the Pólya urn problem.

13 pages, 14 figures

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Emergence of $q$-statistical functions in a generalized binomial distribution with strong correlations · wovepaper