Emergence of $q$-statistical functions in a generalized binomial distribution with strong correlations
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 P\'{o}lya urn problem.
Keywords
Cite
@article{arxiv.1412.0006,
title = {Emergence of $q$-statistical functions in a generalized binomial distribution with strong correlations},
author = {Guiomar Ruiz and Constantino Tsallis},
journal= {arXiv preprint arXiv:1412.0006},
year = {2015}
}
Comments
13 pages, 14 figures