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We consider the long-time behavior of a diffusion process on $\mathbb{R}^d$ advected by a stationary random vector field which is assumed to be divergence-free, dihedrally symmetric in law and have a log-correlated potential. A special case…

Probability · Mathematics 2024-09-19 Scott Armstrong , Ahmed Bou-Rabee , Tuomo Kuusi

In this paper we study the large deviations of time averaged mean square displacement (TAMSD) for Gaussian processes. The theory of large deviations is related to the exponential decay of probabilities of large fluctuations in random…

Probability · Mathematics 2018-11-29 J. Gajda , A. Wylomanska , H. Kantz , A. V. Chechkin , G. Sikora

The statistical inverse problem of estimating the probability distribution of an infinite-dimensional unknown given its noisy indirect observation is studied in the Bayesian framework. In practice, one often considers only…

Statistics Theory · Mathematics 2017-11-21 Sari Lasanen

We introduce a four-parameter extended family of distributions related to the wrapped Cauchy distribution on the circle. The proposed family can be derived by altering the settings of a problem in Brownian motion which generates the wrapped…

Statistics Theory · Mathematics 2013-02-04 Shogo Kato , M. C. Jones

In problems with large amounts of missing data one must model two distinct data generating processes: the outcome process which generates the response and the missing data mechanism which determines the data we observe. Under the…

Methodology · Statistics 2021-11-10 Antonio R. Linero

We construct a class of one-dimensional diffusion processes on the particles of branching Brownian motion that are symmetric with respect to the limits of random martingale measures. These measures are associated with the extended extremal…

Probability · Mathematics 2018-11-07 Sebastian Andres , Lisa Hartung

The probability density is a fundamental quantity for characterizing diffusion processes. However, it is seldom known except in a few renowned cases, including Brownian motion and the Ornstein-Uhlenbeck process and their bridges, geometric…

Mathematical Physics · Physics 2024-03-05 Alain Mazzolo

We establish an integral test describing the exact cut-off between recurrence and transience for normally reflected Brownian motion in certain unbounded domains in a class of warped product manifolds. Besides extending a previous result by…

Differential Geometry · Mathematics 2016-08-24 Levi Lopes de Lima

We construct a model of Brownian Motion on a pseudo-Riemannian manifold associated with general relativity. There are two aspects of the problem: The first is to define a sequence of stopping times associated with the Brownian "kicks" or…

General Physics · Physics 2013-04-02 Paul O'Hara , Lamberto Rondoni

In a general class of Bayesian nonparametric models, we prove that the posterior distribution can be asymptotically approximated by a Gaussian process. Our results apply to nonparametric exponential family that contains both Gaussian and…

Statistics Theory · Mathematics 2017-11-01 Zuofeng Shang , Guang Cheng

A possible mechanism leading to anomalous diffusion is the presence of long-range correlations in time between the displacements of the particles. Fractional Brownian motion, a non-Markovian self-similar Gaussian process with stationary…

Statistical Mechanics · Physics 2019-04-03 Alexander H O Wada , Alex Warhover , Thomas Vojta

Nonergodicity observed in single-particle tracking experiments is usually modeled by transient trapping rather than spatial disorder. We introduce models of a particle diffusing in a medium consisting of regions with random sizes and random…

Soft Condensed Matter · Physics 2014-09-23 P. Massignan , C. Manzo , J. A. Torreno-Pina , M. F. García-Parajo , M. Lewenstein , G. J. Lapeyre

We show that when Brownian motion takes place in a heterogeneous medium, the presence of local forces and transport coefficients leads to deviations from a Gaussian probability distribution that make that the ratio between forward and…

Soft Condensed Matter · Physics 2016-12-21 Paolo Malgaretti , Ignacio Pagonabarraga Miguel J. Rubi

In the context of non-Gaussian analysis, Schneider [27] introduced grey noise measures, built upon Mittag-Leffler functions; analogously, grey Brownian motion and its generalizations were constructed (see, for example, [25], [6], [7], [8]).…

Probability · Mathematics 2022-07-28 Luisa Beghin , Lorenzo Cristofaro , Janusz Gajda

As represented by the Liouville measure, Gaussian multiplicative chaos is a random measure constructed from a Gaussian field. Under certain technical assumptions, we prove the convergence of a process time-changed by Gaussian multiplicative…

Probability · Mathematics 2024-10-02 Takumu Ooi

Measurements of protein motion in living cells and membranes consistently report transient anomalous diffusion (subdiffusion) which converges back to a Brownian motion with reduced diffusion coefficient at long times, after the anomalous…

Quantitative Methods · Quantitative Biology 2015-06-05 Hédi Soula , Bertrand Caré , Guillaume Beslon , Hugues Berry

Wang et al. [PNAS 106 (2009) 15160] have found that in several systems the linear time dependence of the mean-square displacement (MSD) of diffusing colloidal particles, typical of normal diffusion, is accompanied by a non-Gaussian…

Statistical Mechanics · Physics 2015-06-19 Mykyta V. Chubynsky , Gary W. Slater

We show that the uniform norm of generalized grey Brownian motion over the unit interval has an analytic density, excluding the special case of fractional Brownian motion. Our main result is an asymptotic expansion for the small ball…

Probability · Mathematics 2023-01-13 Stefan Gerhold

This paper is a step in the direction of understanding the behavior of non-intersecting Brownian motions on the real line, when the number of particles becomes large. Consider 2k non-intersecting Brownian motions, all starting at the…

Probability · Mathematics 2007-05-23 Mark Adler , Pierre van Moerbeke

Statistical inference as a formal scientific method to covert experience to knowledge has proven to be elusively difficult. While frequentist and Bayesian methodologies have been accepted in the contemporary era as two dominant schools of…

Statistics Theory · Mathematics 2023-01-16 Chuanhai Liu , Ryan Martin