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In this paper we investigate the class of grey Brownian motions $B_{\alpha,\beta}$ ($0<\alpha<2$, $0<\beta\leq1$). We show that grey Brownian motion admits different representations in terms of certain known processes, such as fractional…

Probability · Mathematics 2017-08-23 José Luís Da Silva , Mohamed Erraoui

Several long-time limit theorems of one-dimensional L\'{e}vy processes weighted and normalized by functions of the local time are studied. The long-time limits are taken via certain families of random times, called clocks: exponential…

Probability · Mathematics 2023-01-18 Shosei Takeda , Kouji Yano

We consider the minimization over probability measures of the expected value of a random variable, regularized by relative entropy with respect to a given probability distribution. In the general setting we provide a complete…

Probability · Mathematics 2020-09-29 Joris Bierkens , Hilbert J. Kappen

Passive scalar motion in a family of random Gaussian velocity fields with long-range correlations is shown to converge to persistent fractional Brownian motions in long times.

Probability · Mathematics 2007-05-23 Albert Fannjiang , Tomasz Komorowski

We obtain a formula for the density of the winding number of planar Brownian motion around the origin, and deduce from it asymptotic expansions in inverse powers of the logarithm of the squared time, explicit in the angular variable. In…

Probability · Mathematics 2012-10-08 Stella Brassesco , Silvana C. García Pire

Long-time limit of one-dimensional L\'{e}vy processes weighted and normalized with respect to the exponential functional of two-point local times are studied. The limit processes may vary according to the choice of random clocks.

Probability · Mathematics 2024-05-02 Kohki Iba , Kouji Yano

We summarize the results of investigating the asymptotic behavior of the weighted quantile correlation tests for the location-scale family associated to the logistic distribution. Explicit representations of the limiting distribution are…

Statistics Theory · Mathematics 2014-04-03 Ferenc Balogh , Eva Krauczi

In this paper, we first consider the parameter estimation of a multivariate random process distribution using multivariate Gaussian mixture law. The labels of the mixture are allowed to have a general probability law which gives the…

Data Analysis, Statistics and Probability · Physics 2009-11-07 Hichem Snoussi , Ali Mohammad-Djafari

Different change-point type models encountered in statistical inference for stochastic processes give rise to different limiting likelihood ratio processes. In this paper we consider two such likelihood ratios. The first one is an…

Statistics Theory · Mathematics 2010-04-05 Serguei Dachian

We establish the scaling limit of a class of boundary random walks to the full spectrum of Brownian-type processes on the half-line. By solving the associated martingale problem and employing weak convergence techniques, we prove that under…

Probability · Mathematics 2025-10-03 Juan Carlos Arroyave , Eldon Barros , Eduardo Pimenta

We prove a convergence theorem for a sequence of super-Brownian motions moving among hard Poissonian obstacles, when the intensity of the obstacles grows to infinity but their diameters shrink to zero in an appropriate manner. The…

Probability · Mathematics 2009-06-10 Amandine Veber

In this paper, we establish limit theorems for the supremum of the support, denoted by $M_t$, of a supercritical super-Brownian motion $\{X_t, t\ge0\}$ on $\mathbb{R}$. We prove that there exists an $m(t)$ such that $(X_t-m(t), M_t-m(t))$…

Probability · Mathematics 2020-11-04 Yan-Xia Ren , Renming Song , Rui Zhang

Consider the invariance principle for a random walk with random environment (denoted by $\mu$) in time on $\bfR$ in a weak quenched sense. We show that a sequence of the random probability measures on $\bfR$ generated by a bounded Lipschitz…

Probability · Mathematics 2023-03-14 You Lv , Wenming Hong

In recent years, Bayesian inference in large-scale inverse problems found in science, engineering and machine learning has gained significant attention. This paper examines the robustness of the Bayesian approach by analyzing the stability…

Machine Learning · Statistics 2023-03-06 Alfredo Garbuno-Inigo , Tapio Helin , Franca Hoffmann , Bamdad Hosseini

The paper addresses Brownian motion in the logarithmic potential with time-dependent strength, $U(x,t) = g(t) \log(x)$, subject to the absorbing boundary at the origin of coordinates. Such model can represent kinetics of…

Statistical Mechanics · Physics 2015-09-29 Artem Ryabov , Ekaterina Berestneva , Viktor Holubec

We prove the convergence of the extremal processes for variable speed branching Brownian motions where the "speed functions", that describe the time-inhomogeneous variance, lie strictly below their concave hull and satisfy a certain weak…

Probability · Mathematics 2015-04-15 Anton Bovier , Lisa Hartung

We describe a new construction of a family of measures on a group with the same Poisson boundary. Our approach is based on applying Markov stopping times to an extension of the original random walk.

Probability · Mathematics 2012-09-20 Behrang Forghani

The Brownian motion $(U^N_t)_{t\ge 0}$ on the unitary group converges, as a process, to the free unitary Brownian motion $(u_t)_{t\ge 0}$ as $N\to\infty$. In this paper, we prove that it converges strongly as a process: not only in…

Probability · Mathematics 2019-03-05 Benoit Collins , Antoine Dahlqvist , Todd Kemp

Starting from the hyperbolic Brownian motion as a time-changed Brownian motion, we explore a set of probabilistic models--related to the SABR model in mathematical finance--which can be obtained by geometry-preserving transformations, and…

Probability · Mathematics 2016-10-19 Archil Gulisashvili , Blanka Horvath , Antoine Jacquier

Behavioural economics provides labels for patterns in human economic behaviour. Probability weighting is one such label. It expresses a mismatch between probabilities used in a formal model of a decision (i.e. model parameters) and…

Theoretical Economics · Economics 2020-05-04 Ole Peters , Alexander Adamou , Mark Kirstein , Yonatan Berman