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The Levy diffusion processes are a form of non ordinary statistical mechanics resting, however, on the conventional Markov property. As a consequence of this, their dynamic derivation is possible provided that (i) a source of randomness is…

Statistical Mechanics · Physics 2016-08-31 Mauro Bologna , Paolo Grigolini , Juri Riccardi

In this paper, we study some aspects on random analysis on the L\'eevy stochastic processes with margins following generalized hyperbolic distributions generated by gamma laws. In particular we study the boundedness of its total variations…

Probability · Mathematics 2022-12-14 Nafy Ngom , Aladji Babacar Niang , Soumaila Dembele , Gane Samb Lo

Transformation-based methods have been an attractive approach in non-parametric inference for problems such as unconditional and conditional density estimation due to their unique hierarchical structure that models the data as flexible…

Statistics Theory · Mathematics 2020-11-06 Sean Plummer , Shuang Zhou , Anirban Bhattacharya , David Dunson , Debdeep Pati

Nonlinear conservation laws driven by L\'evy processes have solutions which, in the case of supercritical nonlinearities, have an asymptotic behavior dictated by the solutions of the linearized equations. Thus the explicit representation of…

Mathematical Physics · Physics 2015-10-09 K. Górska , W. A. Woyczynski

Generalization of the integral representation of the gamma function has been obtained, which shows that the Hankel contour assumes rotation in the complex plane. The range of admissible values for the contour rotation angle is set. Using…

Classical Analysis and ODEs · Mathematics 2021-07-22 Viacheslav V. Saenko

The main purpose of this note is to point out the relevance of the Mittag-Leffler probability distribution in the so-called thinning theory for a renewal process with a queue of power law type. This theory, formerly considered by Gnedenko…

Probability · Mathematics 2018-08-21 Rudolf Gorenflo , Francesco Mainardi

The functional method to derive the fractional Fokker-Planck equation for probability distribution from the Langevin equation with Levy stable noise is proposed. For the Cauchy stable noise we obtain the exact stationary probability density…

Statistical Mechanics · Physics 2008-10-07 A. A. Dubkov , B. Spagnolo

The spectrum profile that emerges in molecular spectroscopy and atmospheric radiative transfer as the combined effect of Doppler and pressure broadenings is known as the Voigt profile function. Because of its convolution integral…

Mathematical Physics · Physics 2008-06-12 Gianni Pagnini , Francesco Mainardi

We have provided a fractional generalization of the Poisson renewal processes by replacing the first time derivative in the relaxation equation of the survival probability by a fractional derivative of order $\alpha ~(0 < \alpha \leq 1)$. A…

Statistics Theory · Mathematics 2013-08-01 Nicy Sebastian , Rudolf Gorenflo

We briefly review Boltzmann-Gibbs and nonextensive statistical mechanics as well as their connections with Fokker-Planck equations and with existing central limit theorems. We then provide some hints that might pave the road to the proof of…

Statistical Mechanics · Physics 2009-09-29 Constantino Tsallis

An interesting line of research is the investigation of the laws of random variables known as Dirichlet means. However, there is not much information on interrelationships between different Dirichlet means. Here, we introduce two…

Statistics Theory · Mathematics 2010-10-11 Lancelot F. James

The so-called Pareto-Levy or power-law distribution has been successfully used as a model to describe probabilities associated to extreme variations of worldwide stock markets indexes data and it has the form $Pr(X>x) ~ x**(-alpha) for…

Other Condensed Matter · Physics 2009-11-10 H. F. Coronel-Brizio , A. R. Hernandez-Montoya

We study a class of observables in four-dimensional superconformal Yang--Mills theories which, in the planar limit at finite 't Hooft coupling, can be expressed as determinants of semi-infinite matrices built from Bessel functions. This…

High Energy Physics - Theory · Physics 2025-08-29 G. P. Korchemsky

We prove that weakly continuous solutions to martingale problems admit a canonical regular conditional probability distribution. This allows for the construction of time consistent convex dynamic procedures in a non dominated setting.…

Probability · Mathematics 2012-10-09 Jocelyne Bion-Nadal

This paper develops a threshold regression model where an unknown relationship between two variables nonparametrically determines the threshold. We allow the observations to be cross-sectionally dependent so that the model can be applied to…

Econometrics · Economics 2021-01-29 Yoonseok Lee , Yulong Wang

We analyze the posterior contraction rates of parameters in Bayesian models via the Langevin diffusion process, in particular by controlling moments of the stochastic process and taking limits. Analogous to the non-asymptotic analysis of…

Statistics Theory · Mathematics 2022-08-18 Wenlong Mou , Nhat Ho , Martin J. Wainwright , Peter Bartlett , Michael I. Jordan

We consider the large deviations associated with the empirical mean of independent and identically distributed random variables under a subexponential moment condition. We show that non-trivial deviations are observable at a subexponential…

Probability · Mathematics 2025-07-22 Grégoire Ferré

We introduce a persistent random walk model with finite velocity and self-reinforcing directionality, which explains how exponentially distributed runs self-organize into truncated L\'evy walks observed in active intracellular transport by…

Statistical Mechanics · Physics 2024-02-07 Daniel Han , Marco A. A. da Silva , Nickolay Korabel , Sergei Fedotov

The nonextensive statistical ensembles are revisited for the complex systems with long-range interactions and long-range correlations. An approximation, the value of nonextensive parameter (1-q) is assumed to be very tiny, is adopted for…

Statistical Mechanics · Physics 2020-02-26 Yahui Zheng , Jiulin Du , Linxia Liu , Huijun Kong

We revisit logistic regression and its nonlinear extensions, including multilayer feedforward neural networks, by showing that these classifiers can be viewed as converting input or higher-level features into Dempster-Shafer mass functions…

Machine Learning · Computer Science 2019-12-13 Thierry Denoeux
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