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In this paper we show a some new look at large deviation theorems from the viewpoint of the information-spectrum (IS) methods, which has been first exploited in information theory, and also demonstrate a new basic formula for the large…

Information Theory · Computer Science 2007-07-13 Te Sun Han

The q-exponential distributions, which are generalizations of the Zipf-Mandelbrot power-law distribution, are frequently encountered in complex systems at their stationary states. From the viewpoint of the principle of maximum entropy, they…

Statistical Mechanics · Physics 2009-11-07 Sumiyoshi Abe

We link, by means of a semiclassical approach, the fractional statistics of particles obeying the Haldane exclusion principle to the Tsallis statistics and derive a generalized quantum entropy and its associated statistics.

High Energy Physics - Theory · Physics 2015-06-26 G. Kaniadakis , A. Lavagno , P. Quarati

Fully Probabilistic design (FPD) is a powerful framework offering an elegant and unifying account of stochastic control, learning and decision-making. Here we introduce a generalized FPD framework, which we term as Tsallis FPD. Tsallis FPD…

Optimization and Control · Mathematics 2026-05-18 Vyacheslav Kungurtsev , Giovanni Russo

The function $y=\Phi_\alpha(x)$, the solution of $y^\alpha e^y=x$ for $x$ and $y$ large enough, has a series expansion in terms of $\ln x$ and $\ln\ln x$, with coefficients given in terms of Stirling cycle numbers. It is shown that this…

Classical Analysis and ODEs · Mathematics 2008-02-03 David J. Jeffrey , Robert M. Corless , David E. G. Hare , Donald E. Knuth

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský

The behavior of stock market returns over a period of 1-60 days has been investigated for S&P 500 and Nasdaq within the framework of nonextensive Tsallis statistics. Even for such long terms, the distributions of the returns are…

Statistical Finance · Quantitative Finance 2017-09-18 Sandhya Devi

The coupled entropy is proven to correct a flaw in the derivation of the Tsallis entropy and thereby solidify the theoretical foundations for analyzing the uncertainty of complex systems. The Tsallis entropy originated from considering…

Machine Learning · Statistics 2025-11-25 Kenric P. Nelson

We demonstrate that selection of the minimal value of ordered variables leads in a natural way to its distribution being given by the Tsallis distribution, the same as that resulting from Tsallis nonextensive statistics. The possible…

Statistical Mechanics · Physics 2009-11-13 G. Wilk , Z. Wlodarczyk

The different between the inverse power function and the negative exponential function is significant. The former suggests a complex distribution, while the latter indicates a simple distribution. However, the association of the power-law…

Physics and Society · Physics 2018-12-19 Yanguang Chen

Based on the generalized Boltzmann equation and the reverse function of the distribution function, we investigate the two-parameter generalized statistics and get an expression between the two parameters (k,r) and the physical quantities…

Statistical Mechanics · Physics 2015-08-10 Lina Guo , Jiulin Du

In many applications in biology, engineering and economics, identifying similarities and differences between distributions of data from complex processes requires comparing finite categorical samples of discrete counts. Statistical…

Methodology · Statistics 2023-07-11 Francesco Camaglia , Ilya Nemenman , Thierry Mora , Aleksandra M. Walczak

Classical and quantum Tsallis distributions have been widely used in many branches of natural and social sciences. But, the quantum field theory of the Tsallis distributions is relatively a less explored arena. In this article we derive the…

High Energy Physics - Phenomenology · Physics 2020-01-07 Mahfuzur Rahaman , Trambak Bhattacharyya , Jan-e Alam

Taylor's law (TL) states that the variance $V$ of a non-negative random variable is a power function of its mean $M$, i.e. $V=a M^b$. The ubiquitous empirical verification of TL, typically displaying sample exponents $b \simeq 2$, suggests…

Populations and Evolution · Quantitative Biology 2016-02-17 Andrea Giometto , Marco Formentin , Andrea Rinaldo , Joel E. Cohen , Amos Maritan

In reaction rate theory, in input-output type models and in reaction-diffusion problems when the total derivatives are replaced by fractional derivatives the solutions are obtained in terms of Mittag-Leffler functions and their…

Statistical Mechanics · Physics 2011-03-01 A. M. Mathai , H. J. Haubold

If the generalized statistics suggested by Tsallis are used in statistical mechanics, the fluctuation-dissipation theorem no longer holds. Only in the limiting case where Boltzmann statistics are recovered is the theorem applicable. In…

Superconductivity · Physics 2007-05-23 H. Uys , H. G. Miller

In a family of random variables, Taylor's law or Taylor's power law offluctuation scaling is a variance function that gives the variance $\sigma^{2}>0$ of a random variable (rv) $X$ with expectation $\mu >0$ as a powerof $\mu$: $\sigma…

Probability · Mathematics 2022-08-10 Joel E. Cohen , Thierry E Huillet

In two recent articles we have examined a generalization of the binomial distribution associated with a sequence of positive numbers, involving asymmetric expressions of probabilities that break the symmetry {\it win-loss}. We present in…

Mathematical Physics · Physics 2015-06-17 H. Bergeron , E. M. F. Curado , J. P. Gazeau , Ligia M. C. S. Rodrigues

In the present paper, the author discusses the derivation of unit distributions and the derivation of the generalized form using the order statistics. The author discusses the Kumaraswamy as the smallest order statistic of the unit power…

Methodology · Statistics 2025-09-17 Iman Mohamed Attia

Discrete normal distributions are defined as the distributions with prescribed means and covariance matrices which maximize entropy on the integer lattice support. The set of discrete normal distributions form an exponential family with…

Information Theory · Computer Science 2022-01-25 Frank Nielsen
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