Bivariate superstatistics based on generalized gamma distribution

The univariate gamma (chi-squared) superstatistics has been used in several applications by assuming independence between systems. However, in some cases it seems more reasonable to consider a dependence structure. This fact motivates the introduction of a family of bivariate superstatistics based o...

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Bibliographic Details
Published in:The European physical journal. B, Condensed matter physics Condensed matter physics, 2020-03, Vol.93 (3), Article 43
Main Authors: Caamaño-Carrillo, Christian, Contreras-Reyes, Javier E., González-Navarrete, Manuel, Sánchez, Ewin
Format: Article
Language:English
Subjects:
Bivariate analysis
Complex Systems
Condensed Matter Physics
Fluid- and Aerodynamics
Hypergeometric functions
Mathematical analysis
Physics
Physics and Astronomy
Probability distribution functions
Regular Article
Solid State Physics
Statistical analysis
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Summary:The univariate gamma (chi-squared) superstatistics has been used in several applications by assuming independence between systems. However, in some cases it seems more reasonable to consider a dependence structure. This fact motivates the introduction of a family of bivariate superstatistics based on an extension of the gamma distribution, defined by generalized hypergeometric functions. The particular cases include Boltzmann and other statistical weighting factors in the literature. Numerical illustrations show the behaviour of the proposed superstatistics. Graphical abstract
ISSN:1434-6028
1434-6036
DOI:10.1140/epjb/e2020-100606-8