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This article presents a modern deterministic framework for the study of leading significant digit distributions in numerical data. Rather than relying on traditional probabilistic or mixture-based explanations, we demonstrate that the…

Machine Learning · Statistics 2025-08-20 Vladimir Berman

Maxwell's velocity distribution is known to be universally valid across systems and phases. Here we present a new and general derivation that uses the central limit theorem (CLT) of the probability theory. This essentially uses the idea…

Statistical Mechanics · Physics 2022-06-13 Sangita Mondal , Biman Bagchi

Power-law distributions are common, particularly in social physics. Here, we explore whether power-laws might arise as a consequence of a general variational principle for stochastic processes. We describe communities of 'social particles',…

Physics and Society · Physics 2011-12-30 G. J. Peterson , K. A. Dill

A Wright function based framework is proposed to combine and extend several distribution families. The $\alpha$-stable distribution is generalized by adding the degree of freedom parameter. The PDF of this two-sided super distribution…

Statistical Finance · Quantitative Finance 2025-02-18 Stephen H. Lihn

Liouville's theorem, based on the Hamiltonian flow (micro-canonical ensemble) for a many particle system, indicates that the (stationary) equilibrium probability distribution is a function of the Hamiltonian. A canonical ensemble…

Statistical Mechanics · Physics 2012-11-21 A. Bhattacharyay

We generalise the distribution semantics underpinning probabilistic logic programming by distilling its essential concept, the separation of a free random component and a deterministic part. This abstracts the core ideas beyond logic…

Artificial Intelligence · Computer Science 2024-05-17 Felix Weitkämper

Power-law distributions with various exponents are studied. We first introduce a simple and generic model that reproduces Zipf's law. We can regard this model both as the time evolution of the population of cities and that of the asset…

Statistical Mechanics · Physics 2007-05-23 Kenji Kawamura , Naomichi Hatano

One of the main contributions of this paper is to illustrate how large deviation theory can be used to determine the equilibrium distribution of a basic droplet model that underlies a number of important models in material science and…

Probability · Mathematics 2015-09-11 Richard S. Ellis , Shlomo Ta'asan

Large-momentum effective theory (LaMET) provides an approach to directly calculate the $x$-dependence of generalized parton distributions (GPDs) on a Euclidean lattice through power expansion and a perturbative matching. When a parton's…

High Energy Physics - Phenomenology · Physics 2025-07-29 Jack Holligan , Huey-Wen Lin , Rui Zhang , Yong Zhao

Power-law distributions are typical macroscopic features occurring in almost all complex systems observable in nature. As a result, researchers in quantitative analyses must often generate random synthetic variates obeying power-law…

Physics and Society · Physics 2014-11-11 Filippo Radicchi

In the last years, researchers have realized the difficulties of fitting power-law distributions properly. These difficulties are higher in Zipf's systems, due to the discreteness of the variables and to the existence of two representations…

Data Analysis, Statistics and Probability · Physics 2022-11-29 Alvaro Corral , Isabel Serra , Ramon Ferrer-i-Cancho

We investigate properties of the particle distribution near the tip of one-dimensional branching random walks at large times $t$, focusing on unusual realizations in which the rightmost lead particle is very far ahead of its expected…

Statistical Mechanics · Physics 2020-08-07 A. H. Mueller , S. Munier

The quasi-transverse-momentum dependent (qTMD) distributions are equal-time correlators that can be computed within the lattice QCD approach. In the regime of large hadron's momentum, qTMD distributions are expressed in terms of standard…

High Energy Physics - Phenomenology · Physics 2023-04-27 Simone Rodini , Alexey Vladimirov

We establish the Level-1 and Level-3 Large Deviation Principles (LDPs) for invariant measures on shift spaces over finite alphabets under very general decoupling conditions for which the thermodynamic formalism does not apply. Such…

Mathematical Physics · Physics 2019-06-28 Noé Cuneo , Vojkan Jakšić , Claude-Alain Pillet , Armen Shirikyan

The Large Deviations Principle (LDP) is verified for a homogeneous diffusion process with respect to a Brownian motion $B_t$, $$ X^\eps_t=x_0+\int_0^tb(X^\eps_s)ds+ \eps\int_0^t\sigma(X^\eps_s)dB_s, $$ where $b(x)$ and $\sigma(x)$ are are…

Probability · Mathematics 2011-08-24 P. Chigansky , R. Liptser

In \cite{FTD1}, we proved the almost sure convergence of eigenvalues of the SYK model, which can be viewed as a type of \emph{law of large numbers} in probability theory; in \cite{FTD2}, we proved that the linear statistic of eigenvalues…

Mathematical Physics · Physics 2018-06-17 Renjie Feng , Gang Tian , Dongyi Wei

In this paper, we show that the basic results in large deviations theory hold for general monetary risk measures, which satisfy the crucial property of max-stability. A max-stable monetary risk measure fulfills a lattice homomorphism…

Functional Analysis · Mathematics 2020-08-19 Michael Kupper , José Miguel Zapata

In this paper, we study the large deviation principle (LDP) for two types (Type I and Type II) of multiplicative Ising models. For Types I and II, the explicit formulas for the free energy functions and the associated rate functions are…

Dynamical Systems · Mathematics 2023-05-16 Jung-Chao Ban , Wen-Guei Hu , Zongfan Zhang

Under the classical long-span asymptotic framework we develop a class of Generalized Laplace (GL) inference methods for the change-point dates in a linear time series regression model with multiple structural changes analyzed in, e.g., Bai…

Statistics Theory · Mathematics 2023-06-22 Alessandro Casini , Pierre Perron

One method to generate random permutations involves using Gaussian elimination with partial pivoting (GEPP) on a random matrix $A$ and storing the permutation matrix factor $P$ from the resulting GEPP factorization $PA=LU$. We are…

Probability · Mathematics 2024-11-19 John Peca-Medlin , Chenyang Zhong
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