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In this paper, we derive tail approximations of integrals of exponential functions of Gaussian random fields with varying mean functions and approximations of the associated point processes. This study is motivated naturally by multiple…

Statistics Theory · Mathematics 2011-12-05 Jingchen Liu , Gongjun Xu

By extrapolating the explicit formula of the zero-bias distribution occurring in the context of Stein's method, we construct characterization identities for a large class of absolutely continuous univariate distributions. Instead of trying…

Statistics Theory · Mathematics 2021-02-26 Steffen Betsch , Bruno Ebner

We derive a large deviation principle for families of random variables in the basin of attraction of spectrally positive stable distributions by proving a uniform version of the Tauberian theorem for Laplace-Stieltjes transforms. The main…

Probability · Mathematics 2026-05-25 Giampaolo Cristadoro , Gaia Pozzoli

A number of recent studies have estimated the inter-galactic void probability function and investigated its departure from various random models. We study a family of parametric statistical models based on gamma distributions, which do give…

Mathematical Physics · Physics 2008-11-27 C. T. J. Dodson

In this paper, the sum of L independent but not necessarily identically distributed (i.n.i.d.) extended $\eta$-$\mu$ variates is considered. In particular, novel expressions for the probability density function and cumulative distribution…

Signal Processing · Electrical Eng. & Systems 2021-08-25 Osamah S. Badarneh , Fares S. Almehmadi

In this paper we study the Exponentiated Hypoexponential Distribution with different parameters. The distribution added a parameter to the n parameters of the Hypoexponenial distribution. We first derive a closed expression of the…

Methodology · Statistics 2023-08-03 Anass Nassabein , Therrar Kadri , Seifideen Kadry , Khaled Smaili

We consider the asymmetric random average process which is a one-dimensional stochastic lattice model with nearest neighbour interaction but continuous and unbounded state variables. First, the explicit functional representations, so-called…

Statistical Mechanics · Physics 2009-11-07 Frank Zielen , Andreas Schadschneider

We propose a method for deterministic sampling of arbitrary continuous angular density functions. With deterministic sampling, good estimation results can typically be achieved with much smaller numbers of samples compared to the commonly…

Systems and Control · Electrical Eng. & Systems 2025-04-03 Daniel Frisch , Uwe D. Hanebeck

We study a new class of so-called rational-infinitely (or quasi-infinitely) divisible probability laws on the real line. The characteristic functions of these distributions are ratios of the characteristic functions of classical infinitely…

Probability · Mathematics 2025-10-29 Alexey Khartov

Over the last 80 years there has been much interest in the problem of finding an explicit formula for the probability density function of two zero mean correlated normal random variables. Motivated by this historical interest, we use a…

Statistics Theory · Mathematics 2021-04-13 Robert E. Gaunt

Context: Two-point correlation functions are used throughout cosmology as a measure for the statistics of random fields. When used in Bayesian parameter estimation, their likelihood function is usually replaced by a Gaussian approximation.…

Cosmology and Nongalactic Astrophysics · Physics 2011-10-07 David Keitel , Peter Schneider

This paper derives the exact transition density and cumulative distribution function of a linear combination of two independent Cox-Ingersoll-Ross (CIR) processes. By combining the Poisson Gamma mixture representation of the noncentral…

Probability · Mathematics 2025-11-03 Bilgi Yilmaz , Alper Hekimoglu

The problem of inferring the distribution of a random vector given that its norm is large requires modeling a homogeneous limiting density. We suggest an approach based on graphical models which is suitable for high-dimensional vectors. We…

Probability · Mathematics 2022-12-20 Adrien Hitz , Robin Evans

We study the probability distribution function of the long-time values of observables being time-evolved by Hamiltonians modeling clean and disordered one-dimensional chains of many spin-1/2 particles. In particular, we analyze the return…

Disordered Systems and Neural Networks · Physics 2023-10-10 I. Vallejo-Fabila , E. Jonathan Torres-Herrera

This work studies the product and ratio statistics of independent and non-identically distributed (i.n.i.d) $ \alpha-\kappa - \mu $ shadowed random variables. We derive the series expression for the probability density function (PDF),…

Information Theory · Computer Science 2024-07-16 Shashank Shekhar , Sheetal Kalyani

We build upon recent advances on the distributional aspect of Stein's method to propose a novel and flexible technique for computing Stein operators for random variables that can be written as products of independent random variables. We…

Probability · Mathematics 2018-09-28 Robert E. Gaunt , Guillaume Mijoule , Yvik Swan

Consider a random matrix $\mathbf{A}\in\mathbb{C}^{m\times n}$ ($m \geq n$) containing independent complex Gaussian entries with zero mean and unit variance, and let $0<\lambda_1\leq \lambda_{2}\leq ...\leq \lambda_n<\infty$ denote the…

Statistics Theory · Mathematics 2012-11-06 Prathapasinghe Dharmawansa , Matthew McKay , Yang Chen

We derive the stationary probability distribution for a non-equilibrium system composed by an arbitrary number of degrees of freedom that are subject to Gaussian colored noise and a conservative potential. This is based on a…

Statistical Mechanics · Physics 2015-06-01 Claudio Maggi , Umberto Marini Bettolo Marconi , Nicoletta Gnan , Roberto Di Leonardo

We introduce a nonparametric way to estimate the global probability density function for a random persistence diagram. Precisely, a kernel density function centered at a given persistence diagram and a given bandwidth is constructed. Our…

Statistics Theory · Mathematics 2018-03-14 Joshua Lee Mike , Vasileios Maroulas

We introduce a powerful analytic method to study the statistics of the number $\mathcal{N}_{\textbf{A}}(\gamma)$ of eigenvalues inside any contour $\gamma \in \mathbb{C}$ for infinitely large non-Hermitian random matrices ${\textbf A}$. Our…

Disordered Systems and Neural Networks · Physics 2021-06-09 Antonio Tonatiúh Ramos Sánchez , Edgar Guzmán-González , Isaac Pérez Castillo , Fernando L. Metz
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