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We study the statistics of near-extreme events of Brownian motion (BM) on the time interval [0,t]. We focus on the density of states (DOS) near the maximum \rho(r,t) which is the amount of time spent by the process at a distance r from the…

Statistical Mechanics · Physics 2013-12-16 Anthony Perret , Alain Comtet , Satya N. Majumdar , Gregory Schehr

Brownian motion is a Gaussian process described by the central limit theorem. However, exponential decays of the positional probability density function $P(X,t)$ of packets of spreading random walkers, were observed in numerous situations…

Statistical Mechanics · Physics 2020-02-18 Eli Barkai , Stanislav Burov

In this paper we study the discrete approximation to Brownian motion with varying dimension (BMVD in abbreviation) introduced in [4] by continuous time random walks on square lattices. The state space of BMVD contains a $2$-dimensional…

Probability · Mathematics 2021-10-26 Shuwen Lou

This paper studies a problem of Bayesian parameter estimation for a sequence of scaled counting processes whose weak limit is a Brownian motion with an unknown drift. The main result of the paper is that the limit of the posterior…

Statistics Theory · Mathematics 2015-03-19 Asaf Cohen

Given a Gaussian random walk (or a Wiener process), possibly with drift, observed through noise, we consider the problem of estimating its first-passage time $\tau_\ell$ of a given level $\ell$ with a stopping time $\eta$ defined over the…

Statistics Theory · Mathematics 2015-03-17 Marat Burnashev , Aslan Tchamkerten

We extend the ideas of (Barbour 1990) and use Stein's method to obtain a bound on the distance between a scaled time-changed random walk and a time-changed Brownian Motion. We then apply this result to bound the distance between a…

Probability · Mathematics 2017-10-05 Mikolaj J. Kasprzak

In this paper, we study the scaling limit of a class of random walks which behave like simple random walks outside of a bounded region around the origin and which are subject to a partial reflection near the origin. If the probability of…

Probability · Mathematics 2018-11-30 Raphael Forien

A random walk (or a Wiener process), possibly with drift, is observed in a noisy or delayed fashion. The problem considered in this paper is to estimate the first time \tau the random walk reaches a given level. Specifically, the p-moment…

Information Theory · Computer Science 2012-03-22 Marat V. Burnashev , Aslan Tchamkerten

We present an exact solution for the probability density function $P(\tau=t_{\min}-t_{\max}|T)$ of the time-difference between the minimum and the maximum of a one-dimensional Brownian motion of duration $T$. We then generalise our results…

Statistical Mechanics · Physics 2020-04-20 Francesco Mori , Satya N. Majumdar , Gregory Schehr

A particle moves randomly over the integer points of the real line. Jumps of the particle outside the membrane (a fixed "locally perturbating set") are i.i.d., have zero mean and finite variance, whereas jumps of the particle from the…

Probability · Mathematics 2015-04-28 Alexander Iksanov , Andrey Pilipenko

We investigate the distribution of the time spent by a random walker to the right of a boundary moving with constant velocity v. For the continuous-time problem (Brownian motion), we provide a simple alternative proof of Newman's recent…

Statistical Mechanics · Physics 2009-11-07 C. Godreche , J. M. Luck

Diffusion models for continuous state spaces based on Gaussian noising processes are now relatively well understood from both practical and theoretical perspectives. In contrast, results for diffusion models on discrete state spaces remain…

Machine Learning · Computer Science 2026-04-02 Giovanni Conforti , Alain Durmus , Le-Tuyet-Nhi Pham , Gael Raoul

We study pathwise approximation of scalar stochastic differential equations at a single point. We provide the exact rate of convergence of the minimal errors that can be achieved by arbitrary numerical methods that are based (in a…

Probability · Mathematics 2007-05-23 Thomas Muller-Gronbach

We establish an invariance principle connecting boundary random walks on $\mathbb N$ with Feller's Brownian motions on $[0,\infty)$. A Feller's Brownian motion is a Feller process on $[0,\infty)$ whose excursions away from the boundary $0$…

Probability · Mathematics 2026-01-22 Liping Li , Zhangjie Wang

The space-time distribution, $Q_A(x,dt d\xi)$ say, of Brownian hitting of a bounded Borel set $A$ of the $d$-dimensional Euclidian space is studied. We derive the asymptotic form of the leading term of the time-derivative $Q_A(x,…

Probability · Mathematics 2017-12-13 Kohei Uchiyama

We analyze the Brownian Motion limit of a prototypical unit step reinforced random-walk on the half line. A reinforced random walk is one which changes the weight of any edge (or vertex) visited to increase the frequency of return visits.…

Probability · Mathematics 2013-10-02 Jerome K. Percus , Ora E. Percus

We establish the discrete approximation to Brownian motion with varying dimension (BMVD in abbreviation) by random walks. The setting is very similar to that in [11], but here we use a different method allowing us to get rid the…

Probability · Mathematics 2021-11-16 Shuwen Lou

We investigate the time average mean square displacement $\overline{\delta^2}(x(t))=\int_0^{t-\Delta}[x(t^\prime+\Delta)-x(t^\prime)]^2 dt^\prime/(t-\Delta)$ for fractional Brownian and Langevin motion. Unlike the previously investigated…

Data Analysis, Statistics and Probability · Physics 2014-01-30 Weihua Deng , Eli Barkai

Consider the all-time maximum of a Brownian motion with negative drift. Assume that this process is sampled at certain points in time, where the time between two consecutive points is rendered by an Erlang distribution with mean $1/\omega$.…

Probability · Mathematics 2013-03-18 A. J. E. M. Janssen , J. S. H. van Leeuwaarden

Discrete flow models (DFMs) have been proposed to learn the data distribution on finite state space, offering a flexible framework as an alternative to discrete diffusion models. A line of recent work has studied samplers for discrete…

Machine Learning · Statistics 2026-05-28 Zhengyan Wan , Yidong Ouyang , Liyan Xie , Hongyuan Zha , Fang Fang , Guang Cheng