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We study the long-time behavior of the probability density associated with the decoupled continuous-time random walk which is characterized by a superheavy-tailed distribution of waiting times. It is shown that if the random walk is…

Statistical Mechanics · Physics 2011-05-02 S. I. Denisov , H. Kantz

Quadratic variations of Gaussian processes play important role in both stochastic analysis and in applications such as estimation of model parameters, and for this reason the topic has been extensively studied in the literature. In this…

Probability · Mathematics 2015-02-06 Lauri Viitasaari

We present an analytical approach to study simple symmetric random walks (RWs) on a crossing geometry consisting of a plane square lattice crossed by $n_l$ number of lines that all meet each other at a single point (the origin) on the…

Statistical Mechanics · Physics 2019-09-02 Reza Sepehrinia , Abbas Ali Saberi , Hor Dashti-Naserabadi

In empirical studies of random walks, continuous trajectories of animals or individuals are usually sampled over a finite number of points in space and time. It is however unclear how this partial observation affects the measured…

Physics and Society · Physics 2018-03-13 Riccardo Gallotti , Rémi Louf , Jean-Marc Luck , Marc Barthelemy

The problem of sums of independent, identically distributed random variables with stretched-exponential tails exhibits a dynamical phase transition and has recently reemerged in the context of active transport and condensation phenomena. We…

Statistical Mechanics · Physics 2026-05-11 Alberto Bassanoni , Omer Hamdi

A Gaussian fluctuation formula is proved for linear statistics of complex random matrices in the case that the statistic is rotationally invariant. For a general linear statistic without this symmetry, Coulomb gas theory is used to predict…

Statistical Mechanics · Physics 2007-05-23 P. J. Forrester

We study distributions of random vectors whose components are second order polynomials in Gaussian random variables. Assuming that the law of such a vector is not absolutely continuous with respect to Lebesgue measure, we derive some…

Probability · Mathematics 2013-05-28 Vladimir I. Bogachev , Egor D. Kosov , Ivan Nourdin , Guillaume Poly

Random advection of Lagrangian tracer scalar field $\theta (t,x)$ by a one-dimensional, spatially smooth and short-correlated in time velocity field is considered. Scalar fluctuations are maintained by a source concentrated at the integral…

chao-dyn · Physics 2009-10-30 M. Chertkov , I. Kolokolov , M. Vegrassola

We experimentally demonstrate that the statistical properties of distances between pedestrians which are hindered from avoiding each other are described by the Gaussian Unitary Ensemble of random matrices. The same result has recently been…

Physics and Society · Physics 2010-02-01 Daniel Jezbera , David Kordek , Jan Kriz , Petr Seba , Petr Sroll

We consider the problem of computing a Gaussian approximation to the posterior distribution of a parameter given a large number N of observations and a Gaussian prior, when the dimension of the parameter d is also large. To address this…

Data Structures and Algorithms · Computer Science 2023-03-28 Marc Lambert , Silvère Bonnabel , Francis Bach

We introduce and initiate the study of new parameters associated with any norm and any log-concave measure on $\mathbb R^n$, which provide sharp distributional inequalities. In the Gaussian context this investigation sheds light to the…

Functional Analysis · Mathematics 2017-10-23 Grigoris Paouris , Petros Valettas

In this paper we study approximations for boundary crossing probabilities for the moving sums of i.i.d. normal random variables. We propose approximating a discrete time problem with a continuous time problem allowing us to apply developed…

Statistics Theory · Mathematics 2019-04-30 Jack Noonan , Anatoly Zhigljavsky

Let $A$ be a matrix whose columns $X_1,\dots, X_N$ are independent random vectors in $\mathbb{R}^n$. Assume that the tails of the 1-dimensional marginals decay as $\mathbb{P}(|\langle X_i, a\rangle|\geq t)\leq t^{-p}$ uniformly in $a\in…

Probability · Mathematics 2015-09-09 Olivier Guédon , Alexander E. Litvak , Alain Pajor , Nicole Tomczak-Jaegermann

We obtain rates of contraction of posterior distributions in inverse problems defined by scales of smoothness classes. We derive abstract results for general priors, with contraction rates determined by Galerkin approximation. The rate…

Statistics Theory · Mathematics 2020-07-15 Shota Gugushvili , Aad van der Vaart , Dong Yan

In this article we refine well-known results concerning the fluctuations of one-dimensional random walks. More precisely, if $(S_n)_{n \geq 0}$ is a random walk starting from 0 and $r\geq 0$, we obtain the precise asymptotic behavior as…

Probability · Mathematics 2013-12-06 Rim Essifi , Marc Peigné , Kilian Raschel

We present large deviations principles for the moments of the empirical spectral measure of Wigner matrices and empirical measure of $\beta$-ensembles in three cases : the case of Wigner matrices without Gaussian tails, that is Wigner…

Probability · Mathematics 2016-05-13 Fanny Augeri

Let (Z_n)_{n\in\N_0} be a d-dimensional random walk in random scenery, i.e., Z_n=\sum_{k=0}^{n-1}Y_{S_k} with (S_k)_{k\in\N_0} a random walk in Z^d and (Y_z)_{z\in Z^d} an i.i.d. scenery, independent of the walk. We assume that the random…

Probability · Mathematics 2016-08-16 Remco van der Hofstad , Nina Gantert , Wolfgang König

Let $T$ be the Student one- or two-sample $t$-, $F$-, or Welch statistic. Now release the underlying assumptions of normality, independence and identical distribution and consider a more general case where one only assumes that the vector…

Statistics Theory · Mathematics 2014-10-23 Dmitrii Zholud

We consider distributional approximation by generalized Dickman distributions, which appear in number theory, perpetuities, logarithmic combinatorial structures and many other areas. We prove bounds in the Kolmogorov distance for the…

Probability · Mathematics 2022-11-21 Chinmoy Bhattacharjee , Matthias Schulte

We study when a given Gaussian random variable on a given probability space $(\Omega, {\cal{F}}, P) $ is equal almost surely to $\beta_{1}$ where $\beta $ is a Brownian motion defined on the same (or possibly extended) probability space. As…

Probability · Mathematics 2009-08-24 Ciprian Tudor
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