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Articles

Beta rank function: A smooth double-Pareto-like distribution

ORCID Icon, , , &
Pages 3645-3668 | Received 31 Oct 2019, Accepted 19 Jul 2020, Published online: 03 Aug 2020
 

Abstract

The beta rank function (BRF), x(u)=A(1u)b/ua, where u is the normalized and continuous rank of an observation x, has wide applications in fitting real-world data. The underlying probability density function (pdf) fX(x) is not expressible in terms of elementary functions except for specific parameter values. We show however that it is approximately a unimodal skewed two-sided power law, or double-Pareto, or log-Laplacian distribution. Analysis of the pdf is simplified when the independent variable is log-transformed; the pdf fZ=logX(z) is smooth at the peak; probability is partitioned by the peak with proportion b/a (left to right); decay on left and right tails is approximately exponential, ezlog(A)b/b and ezlog(A)a/a respectively. On the other hand, fX(x) behaves like a power distribution x1/b1 when x0 and decays like a Pareto 1/x1/a+1 when x0. We give closed-form expressions of both pdf’s in terms of Fox-H functions and propose numerical algorithms to approximate them. We suggest a way to elucidate if a data set follows a one-sided power law, a lognormal, a two-sided power law or a BRF. Finally, we illustrate the usefulness of these distributions in data analysis through a few examples.

Acknowledgements

This paper is dedicated to the memory of Prof. Germinal Cocho, who passed away during the process of its elaboration.

Additional information

Funding

PM acknowledges support from Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México (PAPIIT IN108318). OF is a grant holder of the Dirección General de Asuntos del Personal Académico, Universidad Nacional Autónoma de México - Postdoctoral Scholarships Program at CEIICH, UNAM, working under supervision of Ricardo Mansilla Corona and Aquiles Negrete Yankelevich. WL acknowledges the support from Robert S. Boas Center for Genomics and Human Genetics.

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