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This paper is concerned with making Bayesian inference from data that are assumed to be drawn from a Bingham distribution. A barrier to the Bayesian approach is the parameter-dependent normalising constant of the Bingham distribution,…

Computation · Statistics 2014-01-14 Christopher J. Fallaize , Theodore Kypraios

An amended MaxEnt formulation for systems displaced from the conventional MaxEnt equilibrium is proposed. This formulation involves the minimization of the Kullback-Leibler divergence to a reference $Q$ (or maximization of Shannon…

Mathematical Physics · Physics 2009-11-11 Jean-François Bercher

In this article, the exponentiated discrete Lindley distribution is presented and studied. Some important distributional properties are discussed. Using the maximum likelihood method, estimation of the model parameters is investigated.…

Statistics Theory · Mathematics 2018-07-27 M. El-Morshedy , M. S. Eliwa , H. Nagy

This article considers the application of Langevin dynamics to sampling and investigates how to choose the damping parameter in Langevin dynamics for the purpose of maximizing thoroughness of sampling. Also, it considers the computation of…

Computation · Statistics 2021-06-23 Robert D. Skeel , Carsten Hartmann

Multivariate extreme value statistical analysis is concerned with observations on several variables which are thought to possess some degree of tail-dependence. In areas such as the modeling of financial and insurance risks, or as the…

Applications · Statistics 2014-12-31 Alexis Bienvenüe , Christian Y. Robert

The scaled distribution of the smallest eigenvalue in the Laguerre orthogonal and symplectic ensembles is evaluated in terms of a Painlev\'e V transcendent. This same Painlev\'e V transcendent is known from the work of Tracy and Widom,…

Exactly Solvable and Integrable Systems · Physics 2007-05-23 P. J. Forrester

A Langevin equation with a special type of additive random source is considered. This random force presents a fractional order derivative of white noise, and leads to a power-law time behavior of the mean square displacement of a particle,…

chao-dyn · Physics 2009-10-31 V. Kobelev , E. Romanov

From microscopic models, a Langevin equation can in general be derived only as an approximation. Two possible conditions to validate this approximation are studied. One is, for a linear Langevin equation, that the frequency of the Fourier…

Statistical Mechanics · Physics 2015-05-30 J. Frenkel , J. C. Taylor

Multiplicative self-decomposable laws describe random variables that can be decomposed into a product of a scaled-down version of themselves and an independent residual term. Shanbhag et al.~(1977) have shown that the gamma distribution is…

Probability · Mathematics 2026-01-19 José Luís da Silva , Mohamed Erraoui

Stochastic thermodynamics is a developing theory for systems out of thermal equilibrium. It allows to formulate a wealth of nontrivial relations among thermodynamic quantities such as heat dissipation, excess work, and entropy production in…

Statistical Mechanics · Physics 2026-02-24 Benjamin Sorkin , Gil Ariel , Tomer Markovich

We apply the Frobenius method to the Schr\"{o}dinger equation with a truncated Coulomb potential. By means of the tree-term recurrence relation for the expansion coefficients we truncate the series and obtain exact eigenfunctions and…

Quantum Physics · Physics 2020-08-06 Francisco M. Fernández

In recent papers it has been demonstrated that sampling a Gibbs distribution from an appropriate time-irreversible Langevin process is, from several points of view, advantageous when compared to sampling from a time-reversible one. Adding…

Probability · Mathematics 2015-02-20 Luc Rey-Bellet , Konstantinos Spiliopoulos

We provide an efficient algorithm for the classical problem, going back to Galton, Pearson, and Fisher, of estimating, with arbitrary accuracy the parameters of a multivariate normal distribution from truncated samples. Truncated samples…

Statistics Theory · Mathematics 2020-10-26 Constantinos Daskalakis , Themis Gouleakis , Christos Tzamos , Manolis Zampetakis

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

This work sheds some light on the relationship between a distribution's standard deviation and its range, a topic that has been discussed extensively in the literature. While many previous studies have proposed inequalities or relationships…

Methodology · Statistics 2023-03-14 Roberto Vila , Narayanaswamy Balakrishnan , Raul Matsushita

We consider three classes of linear differential equations on distribution functions, with a fractional order $\alpha\in [0,1].$ The integer case $\alpha =1$ corresponds to the three classical extreme families. In general, we show that…

Probability · Mathematics 2019-08-05 Lotfi Boudabsa , Thomas Simon , Pierre Vallois

We construct the generalized entropy optimized by a given arbitrary statistical distribution with a finite linear expectation value of a random quantity of interest. This offers, via the maximum entropy principle, a unified basis for a…

Statistical Mechanics · Physics 2009-11-07 Sumiyoshi Abe

Several distributions and families of distributions are proposed to model skewed data, think, e.g., of skew-normal and related distributions. Lambert W random variables offer an alternative approach where, instead of constructing a new…

Methodology · Statistics 2023-10-17 Meelis Käärik , Anne Selart , Tuuli Puhkim , Liivika Tee

In this paper, we investigate a continuous time version of the Stochastic Langevin Monte Carlo method, introduced in [WT11], that incorporates a stochastic sampling step inside the traditional over-damped Langevin diffusion. This method is…

Machine Learning · Statistics 2023-01-10 Marelys Crespo Navas , Sébastien Gadat , Xavier Gendre

We calculate exactly the Laplace transform of the Fr\'{e}chet distribution in the form $\gamma x^{-(1+\gamma)} \exp(-x^{-\gamma})$, $\gamma > 0$, $0 \leq x < \infty$, for arbitrary rational values of the shape parameter $\gamma$, i.e. for…

Probability · Mathematics 2015-06-19 K. A. Penson , K. Górska