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For a given normalized Gaussian symmetric matrix-valued process $Y^{(n)}$, we consider the process of its eigenvalues $\{(\lambda_{1}^{(n)}(t),\dots, \lambda_{n}^{(n)}(t)); t\ge 0\}$ as well as its corresponding process of empirical…

Probability · Mathematics 2018-01-09 Arturo Jaramillo , Juan Carlos Pardo , José Luis Pérez

A class of discrete distributions can be derived from stationary renewal processes. They have the useful property that the mean is a simple function of the model parameters. Thus regressions of the distribution mean on covariates can be…

Methodology · Statistics 2018-03-01 Rose Baker

This paper considers the motion of an object subjected to dry friction and an external random force. The objective is to characterize the role of the correlation time of the external random force. We develop efficient stochastic simulation…

Statistical Mechanics · Physics 2023-09-26 Josselin Garnier , Laurent Mertz

We consider the paths of a Gaussian random process $x(t)$, $x(0)=0$ not exceeding a fixed positive level over a large time interval $(0,T)$, $T\gg 1$. The probability $p(T)$ of such event is frequently a regularly varying function at…

Probability · Mathematics 2009-09-29 G. Molchan , A. Khokhlov

We study winding angles of oriented polymers with orientation-dependent interaction in two dimensions. Using exact analytical calculations, computer simulations, and phenomenological arguments, we succeed in finding the variance of the…

Statistical Mechanics · Physics 2009-10-30 Thomas Prellberg , Barbara Drossel

We introduce a Gaussian process-based model for handling of non-stationarity. The warping is achieved non-parametrically, through imposing a prior on the relative change of distance between subsequent observation inputs. The model allows…

Machine Learning · Statistics 2019-12-06 David Tolpin

We consider the semi-parametric estimation of a scale parameter of a one-dimensional Gaussian process with known smoothness. We suggest an estimator based on quadratic variations and on the moment method. We provide asymptotic…

Statistics Theory · Mathematics 2020-01-22 Jean-Marc Azaïs , François Bachoc , Agnès Lagnoux , Thi Mong Ngoc Nguyen

The position $x(t)$ of a particle diffusing in a one-dimensional uncorrelated and time dependent random medium is simply Gaussian distributed in the typical direction, i.e. along the ray $x=v_0 t$, where $v_0$ is the average drift. However,…

Statistical Mechanics · Physics 2021-08-05 Guillaume Barraquand , Pierre Le Doussal

We analyze particle velocity fluctuations in a simulated granular system subjected to homogeneous quasistatic shearing. We show that these fluctuations share the following scaling characteristics of fluid turbulence in spite of their…

Soft Condensed Matter · Physics 2009-11-07 F. Radjai , S. Roux

We discuss continuous cascade models and their potential for modelling the energy dissipation in a turbulent flow. Continuous cascade processes, expressed in terms of stochastic integrals with respect to L\'evy bases, are examples of ambit…

Statistical Mechanics · Physics 2013-05-07 Emil Hedevang , Jürgen Schmiegel

Employing the optimal fluctuation method (OFM), we study the large deviation function of long-time averages $(1/T)\int_{-T/2}^{T/2} x^n(t) dt$, $n=1,2, \dots$, of centered stationary Gaussian processes. These processes are correlated and,…

Statistical Mechanics · Physics 2021-12-13 Baruch Meerson

We investigate granular flows over an inclined rigid base, which is vibrated externally in a direction normal to itself, through discrete element simulations. We vary the base inclination angle theta, vibration frequency f, and amplitude A…

Soft Condensed Matter · Physics 2024-11-12 Prasad Sonar , Ashish Bhateja , Ishan Sharma

This work aims at introducing model methodology and numerical studies related to a Lagrangian stochastic approach applied to the computation of the wind circulation around mills. We adapt the Lagrangian stochastic downscaling method that we…

Computational Engineering, Finance, and Science · Computer Science 2016-11-15 Mireille Bossy , Jose Espina , Jacques Morice , Cristian Paris , Antoine Rousseau

We study the regular conditional law of mixed Gaussian Volterra processes under the influence of model disturbances. More precisely, we study prediction of Gaussian Volterra processes driven by a Brownian motion in a case where the Brownian…

Probability · Mathematics 2019-04-23 Tommi Sottinen , Lauri Viitasaari

We derive rates of contraction of posterior distributions on nonparametric or semiparametric models based on Gaussian processes. The rate of contraction is shown to depend on the position of the true parameter relative to the reproducing…

Statistics Theory · Mathematics 2008-12-18 A. W. van der Vaart , J. H. van Zanten

We study exclusion processes on the integer lattice in which particles change their velocities due to stickiness. Specifically, whenever two or more particles occupy adjacent sites, they stick together for an extended period of time, and…

Probability · Mathematics 2016-08-11 Miklós Z. Rácz , Mykhaylo Shkolnikov

New results on uniform convergence in probability for expansions of Gaussian random processes using compactly supported wavelets are given. The main result is valid for general classes of nonstationary processes. An application of the…

Probability · Mathematics 2013-08-08 Yuriy Kozachenko , Andriy Olenko , Olga Polosmak

Motivated by contemporary and rich applications of anomalous diffusion processes we propose a new statistical test for fractional Brownian motion, which is one of the most popular models for anomalous diffusion systems. The test is based on…

Data Analysis, Statistics and Probability · Physics 2018-10-17 Grzegorz Sikora

We present simulations of granular flows in a modified Couette cell, using a continuum model recently proposed for dense granular flows. Based on a friction coefficient, which depends on an inertial number, the model captures the positions…

Soft Condensed Matter · Physics 2009-11-13 Pierre Jop

Within the framework of the previous paper [8]. we develop a generalized stochastic calculus for processes associated to higher order diffusion operators. Applications to the study of a Cauchy problem, a Feynman-Kac formula and a…

Probability · Mathematics 2016-03-18 Stefano Bonaccorsi , Craig Calcaterra , Sonia Mazzucchi
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