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We investigate the transience/recurrence of a non-Markovian, one-dimensional diffusion process which consists of a Brownian motion with a non-anticipating drift that has two phases---a transient to $+\infty$ mode which is activated when the…

Probability · Mathematics 2012-10-10 Ross G. Pinsky

We provide a detailed description of the structure of the transition probabilities and of the hitting distributions of boundary components of a manifold with corners for a degenerate strong Markov process arising in population genetics. The…

Analysis of PDEs · Mathematics 2017-07-27 Charles L. Epstein , Camelia A. Pop

For an arbitrary diffusion process $X$ with time-homogeneous drift and variance parameters $\mu(x)$ and $\sigma^2(x)$, let $V_\varepsilon$ be $1/\varepsilon$ times the total time $X(t)$ spends in the strip…

Probability · Mathematics 2026-03-03 Nils Lid Hjort , Rafail Zalmonovich Khasminskii

We perform a detailed comparison between a Markov Switching Jump Diffusion Model and a Markov Switching {\alpha}-Stable Distribution Model with respect to the analysis of non-stationary data. We show that the jump diffusion model is…

Applications · Statistics 2016-05-20 Luca Di Persio , Vukasin Jovic

We investigate the extreme value statistics of a one-dimensional Brownian motion (with the diffusion constant $D$) during a time interval $\left[0, t \right]$ in the presence of a reflective boundary at the origin, starting from a positive…

Statistical Mechanics · Physics 2024-01-26 Feng Huang , Hanshuang Chen

The process of diffusion is the most elementary stochastic transport process. Brownian motion, the representative model of diffusion, played a important role in the advancement of scientific fields such as physics, chemistry, biology and…

Statistical Mechanics · Physics 2015-08-11 Alexandre Bovet

We introduce a novel training principle for probabilistic models that is an alternative to maximum likelihood. The proposed Generative Stochastic Networks (GSN) framework is based on learning the transition operator of a Markov chain whose…

Machine Learning · Computer Science 2015-03-29 Guillaume Alain , Yoshua Bengio , Li Yao , Jason Yosinski , Eric Thibodeau-Laufer , Saizheng Zhang , Pascal Vincent

Suppose that particles are randomly distributed in $\bR^d$, and they are subject to identical stochastic motion independently of each other. The Smoluchowski process describes fluctuations of the number of particles in an observation region…

Statistics Theory · Mathematics 2021-08-17 A. Goldenshluger , R. Jacobovic

Simultaneous diffusive and inertial motion of Brownian particles in laminar Couette flow is investigated via Lagrangian and Eulerian descriptions to determine the effect of particle inertia on diffusive transport in the long-time. The…

Statistical Mechanics · Physics 2010-08-13 Yannis Drossinos , Michael W. Reeks

In probability density function (PDF) methods a transport equation is solved numerically to compute the time and space dependent probability distribution of several flow variables in a turbulent flow. The joint PDF of the velocity…

Fluid Dynamics · Physics 2010-06-04 J. Bakosi , P. Franzese , Z. Boybeyi

The presented explanations are provided for the one--dimensional diffusion process with constant drift by using forward Fokker--Planck technique. We are interested in the outflow probability in a finite interval, i.e. first passage time…

Statistical Mechanics · Physics 2007-09-12 Julia Hinkel , Reinhard Mahnke

After a short excursion from discovery of Brownian motion to the Richardson "law of four thirds" in turbulent diffusion, the article introduces the L\'{e}vy flight superdiffusion as a self-similar L\'{e}vy process. The condition of…

Statistical Mechanics · Physics 2015-05-13 A. A. Dubkov , B. Spagnolo , V. V. Uchaikin

We establish the representation of general regular diffusions on star-shaped graphs as time-changed Walsh Brownian motions. These are regular continuous Markov processes described locally by a family generalized second order differential…

Probability · Mathematics 2025-08-01 Alexis Anagnostakis

In grokking, a model first fits the training data while test accuracy remains low, and only later begins to generalize. We ask whether this transition can be localized from observed training trajectories before the test accuracy rises, and…

Machine Learning · Computer Science 2026-05-12 Ziyue Wang , Yufeng Ying , Takafumi Kanamori

For the regime-switching diffusion process with and without advection term we propose an integro-differential equation describing the densities of states continuously distributed over a segment. We demonstrate that there exists a…

Analysis of PDEs · Mathematics 2026-03-18 Alexander S. Bratus , Olga S. Rozanova

Understanding the processes that give rise to quantitative measurements associated with molecular sequence data remains an important issue in statistical phylogenetics. Examples of such measurements include geographic coordinates in the…

Populations and Evolution · Quantitative Biology 2015-12-31 Mandev S. Gill , Lam Si Tung Ho , Guy Baele , Philippe Lemey , Marc A. Suchard

Let $X_1,X_2,\ldots $ be independent random variables observed sequentially and such that $X_1,\ldots,X_{\theta-1}$ have a common probability density $p_0$, while $X_\theta,X_{\theta+1},\ldots $ are all distributed according to $p_1\neq…

Statistics Theory · Mathematics 2018-04-25 Yuri Golubev , Mher Safarian

We study the dynamical properties of the Brownian diffusions having $\sigma {\rm Id}$ as diffusion coefficient matrix and $b=\nabla U$ as drift vector. We characterize this class through the equality $D^2_+=D^2_-$, where $D_{+}$ (resp.…

Probability · Mathematics 2016-08-16 Sébastien Darses , Ivan Nourdin

In the context of order statistics of discrete time random walks (RW), we investigate the statistics of the gap, $G_n$, and the number of time steps, $L_n$, between the two highest positions of a Markovian one-dimensional random walker,…

Statistical Mechanics · Physics 2014-09-17 Satya N. Majumdar , Philippe Mounaix , Gregory Schehr

For one-dimensional Jump-Drift and Jump-Diffusion processes converging towards some steady state, the large deviations of a long dynamical trajectory are described from two perspectives. Firstly, the joint probability of the empirical…

Statistical Mechanics · Physics 2021-08-17 Cecile Monthus