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The quantum statistical parton distributions approach proposed more than one decade ago is revisited by considering a larger set of recent and accurate Deep Inelastic Scattering experimental results. It enables us to improve the description…

High Energy Physics - Phenomenology · Physics 2015-10-22 Jacques Soffer , Claude Bourrely

In this paper, we introduce a risk process, namely, the mixed fractional risk process (MFRP) in which the number of claims in the associated claim process are modelled using the mixed fractional Poisson process (MFPP). The covariance…

Probability · Mathematics 2021-06-23 K. K. Kataria , M. Khandakar

In this paper, we introduce the fractional Fourier series on the fractional torus and study some basic facts of fractional Fourier series, such as fractional convolution and fractional approximation. Meanwhile, fractional Fourier inversion…

Functional Analysis · Mathematics 2024-07-08 Zunwei Fu , Xianming Hou , Qingyan Wu

In the usual Bayesian setting, a full probabilistic model is required to link the data and parameters, and the form of this model and the inference and prediction mechanisms are specified via de Finetti's representation. In general, such a…

Methodology · Statistics 2026-01-21 Yu Luo , David A. Stephens , Daniel J. Graham , Emma J. McCoy

We obtain the state probabilities of various fractional versions of the classical homogeneous Poisson process using an alternate and simpler method known as the Adomian decomposition method (ADM). Generally these state probabilities are…

Probability · Mathematics 2021-07-28 K. K. Kataria , P. Vellaisamy

Fractional calculus allows one to generalize the linear, one-dimensional, diffusion equation by replacing either the first time derivative or the second space derivative by a derivative of fractional order. The fundamental solutions of…

Statistical Mechanics · Physics 2007-05-23 Francesco Mainardi , Paolo Paradisi , Rudolf Gorenflo

In this article, we derive the state probabilities of different type of space- and time-fractional Poisson processes using z-transform. We work on tempered versions of time-fractional Poisson process and space-fractional Poisson processes.…

Probability · Mathematics 2018-08-03 Neha Gupta , Arun Kumar , Nikolai Leonenko

Stacy distribution defined for the first time in 1961 provides a flexible framework for modelling of a wide range of real-life behaviours. It appears under different names in the scientific literature and contains many useful particular…

Probability · Mathematics 2023-03-21 Pavlina K. Jordanova , Mladen Savov , Assen Tchorbadjieff , Milan Stehlík

The joint use of counting functions, Hilbert basis and Markov basis allows to define a procedure to generate all the fractions that satisfy a given set of constraints in terms of orthogonality. The general case of mixed level designs,…

Methodology · Statistics 2009-06-18 Roberto Fontana , Giovanni Pistone

The estimation of parameters in the frequency spectrum of a seasonally persistent stationary stochastic process is addressed. For seasonal persistence associated with a pole in the spectrum located away from frequency zero, a new…

Methodology · Statistics 2007-09-04 Emma J. McCoy , Sofia C. Olhede , David A. Stephens

In this paper we obtain the limit distribution for partial sums with a random number of terms following a class of mixed Poisson distributions. The resulting weak limit is a mixing between a normal distribution and an exponential family,…

Probability · Mathematics 2020-05-08 Wagner Barreto-Souza , Gabriela Oliveira , Roger W. C. Silva

Based on a novel dynamic Whittle likelihood approximation for locally stationary processes, a Bayesian nonparametric approach to estimating the time-varying spectral density is proposed. This dynamic frequency-domain based likelihood…

Methodology · Statistics 2023-03-22 Yifu Tang , Claudia Kirch , Jeong Eun Lee , Renate Meyer

The Humbert-Bessel are multi-index functions with various applications in electromagnetism. New families of functions sharing some similarities with Bessel functions are often introduced in the mathematical literature, but at a closer…

Functional Analysis · Mathematics 2012-12-19 D. Babusci , G. Dattoli , E. Di Palma , E. N. Petropoulou

This paper introduces a generalization of the so-called space-fractional Poisson process by extending the difference operator acting on state space present in the associated difference-differential equations to a much more general form. It…

Probability · Mathematics 2016-03-15 Federico Polito , Enrico Scalas

In this paper, we use a biorthogonal approach (Appell system) to construct and characterize the spaces of test and generalized functions associated to the fractional Poisson measure $\pi_{\lambda,\beta}$, that is, a probability measure in…

Functional Analysis · Mathematics 2022-05-03 Jerome B. Bendong , Sheila M. Menchavez , José Luís da Silva

We study a 2-parametric family of probability measures on an infinite-dimensional simplex (the Thoma simplex). These measures originate in harmonic analysis on the infinite symmetric group (S.Kerov, G.Olshanski and A.Vershik, Comptes Rendus…

Representation Theory · Mathematics 2008-03-02 Grigori Olshanski

In this tutorial survey we recall the basic properties of the special function of the Mittag-Leffler and Wright type that are known to be relevant in processes dealt with the fractional calculus. We outline the major applications of these…

General Mathematics · Mathematics 2021-08-29 Francesco Mainardi

We consider a fractional version of the classical nonlinear birth process of which the Yule--Furry model is a particular case. Fractionality is obtained by replacing the first order time derivative in the difference-differential equations…

Probability · Mathematics 2014-03-06 Enzo Orsingher , Federico Polito

A space fractional diffusion-like equation is introduced, which embodies the nonlocality in time, represented by the memory kernel and the non-locality in space. A specific example of the nonlocal term is considered in combination with…

Statistical Mechanics · Physics 2026-01-06 Pece Trajanovski , Irina Petreska , Katarzyna Gorska , Ljupco Kocarev , Trifce Sandev

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights.…

Applications · Statistics 2016-10-26 Federico Bassetti , Roberto Casarin , Francesco Ravazzolo
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