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In this paper, for the first time a theory is formulated that predicts velocity and spatial correlations between occupation numbers that occur in lattice gas automata violating semi-detailed balance. Starting from a coupled BBGKY hierarchy…

comp-gas · Physics 2009-10-22 H. J. Bussemaker , M. H. Ernst , J. W. Dufty

The Normal Means problem plays a fundamental role in many areas of modern high-dimensional statistics, both in theory and practice. And the Empirical Bayes (EB) approach to solving this problem has been shown to be highly effective, again…

Methodology · Statistics 2018-12-27 Lei Sun , Matthew Stephens

To describe the nonequilibrium states of a system we introduce a new thermodynamic parameter - the lifetime of a system. The statistical distributions which can be obtained out of the mesoscopic description characterizing the behaviour of a…

Statistical Mechanics · Physics 2007-05-23 V. V. Ryazanov

We study the dynamics of a spin-flip model with a mean field interaction. The system is non reversible, spacially inhomogeneous, and it is designed to model social interactions. We obtain the limiting behavior of the empirical averages in…

Probability · Mathematics 2015-05-14 Francesca Collet , Paolo Dai Pra , Elena Sartori

A kinetic inhomogeneous Boltzmann-type equation is proposed to model the dynamics of the number of agents in a large market depending on the estimated value of an asset and the rationality of the agents. The interaction rules take into…

Analysis of PDEs · Mathematics 2017-02-07 Bertram Düring , Ansgar Jüngel , Lara Trussardi

The aim of this review is to provide a concise overview of some of the generic approaches that have been developed to deal with the statistical description of large systems of interacting dissipative 'units'. The latter notion includes,…

Statistical Mechanics · Physics 2017-03-08 Eric Bertin

The consensus problem in distributed computing involves a network of agents aiming to compute the average of their initial vectors through local communication, represented by an undirected graph. This paper focuses on the studying of this…

Optimization and Control · Mathematics 2024-11-26 Nhat Trung Nguyen , Alexander Rogozin , Alexander Gasnikov

We develop a mean-field theory of the growth, exchange and distribution (GED) model introduced by Kang et al. (preceding paper) that accurately describes the phase transition in the limit that the number of agents $N$ approaches infinity.…

Statistical Mechanics · Physics 2021-08-04 W. Klein , N. Lubbers , Kang K. L. Liu , T. Khouw , Harvey Gould

One of the more interesting themes of the mathematical ecology is the description of the mutualistic interaction between two interacting species. Based on continuous-time model developed by Holland and DeAngelis 2009 for consumer-resource…

Populations and Evolution · Quantitative Biology 2015-01-05 Gianluca Gabbriellini

We study the evolution in time of the statistical distribution of some addiction phenomena in a system of individuals. The kinetic approach leads to build up a novel class of Fokker--Planck equations describing relaxation of the probability…

Physics and Society · Physics 2019-10-01 Giuseppe Toscani

Prediction intervals are commonly used in meta-analysis with random-effects models. One widely used method, the Higgins-Thompson-Spiegelhalter prediction interval, replaces the heterogeneity parameter with its point estimate, but its…

Methodology · Statistics 2025-11-14 Kengo Nagashima , Hisashi Noma , Toshi A. Furukawa

We develop new econometric methods for estimation and inference in high-dimensional panel data models with interactive fixed effects. Our approach can be regarded as a non-trivial extension of the very popular common correlated effects…

Econometrics · Economics 2025-08-11 Maximilian Ruecker , Michael Vogt , Oliver Linton , Christopher Walsh

The running-time analysis of evolutionary combinatorial optimization is a fundamental topic in evolutionary computation. However, theoretical results regarding the $(\mu+\lambda)$ evolutionary algorithm (EA) for combinatorial optimization…

Neural and Evolutionary Computing · Computer Science 2025-07-04 Min Huang , Pengxiang Chen , Han Huang , Tongli He , Yushan Zhang , Zhifeng Hao

Stochastic differential equations are widely used in various fields; in particular, the usefulness of duality relations has been demonstrated in some models such as population models and Brownian momentum processes. In this study, a…

Statistical Mechanics · Physics 2021-02-09 Jun Ohkubo

We introduce and discuss a kinetic framework describing the time evolution of the statistical distributions of a population divided into the compartments of susceptible, infectious, recovered, and resistant in the presence of a microbial…

Populations and Evolution · Quantitative Biology 2026-05-07 Marco Menale , Giuseppe Toscani , Mattia Zanella

The Euler and Navier-Stokes fluid mechanics equations are derived using a modified statistical mechanical approach using theory taken from the Chapman-Enskog perturbation analysis used to support the lattice Boltzmann method. Additional…

Fluid Dynamics · Physics 2021-07-06 Charles Cook

We consider the problem of bounding mean first passage times for a class of continuous-time Markov chains that captures stochastic interactions between groups of identical agents. The quantitative analysis of such probabilistic population…

Systems and Control · Electrical Eng. & Systems 2020-04-07 Michael Backenköhler , Luca Bortolussi , Verena Wolf

. We study the evolution of the distribution of eigenvalues of a $N\times N$ matrix subject to a random perturbation drawn from (i) a generalized Gaussian ensemble (ii) a non-Gaussian ensemble with a measure variable under the change of…

Mesoscale and Nanoscale Physics · Physics 2009-10-31 Pragya Shukla

We consider the random walk on a lattice with random transition rates and arbitrarily long-range jumps. We employ Bruggeman's effective medium approximation (EMA) to find the disorder averaged (coarse-grained) dynamics. The EMA procedure…

Disordered Systems and Neural Networks · Physics 2016-07-27 Felix Thiel , Igor M. Sokolov

The problem of assigning probability distributions which objectively reflect the prior information available about experiments is one of the major stumbling blocks in the use of Bayesian methods of data analysis. In this paper the method of…

Data Analysis, Statistics and Probability · Physics 2009-11-10 Ariel Caticha , Roland Preuss
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