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We define weighted fractional Brownian sheets, which are a class of Gaussian random fields with four parameters that include fractional Brownian sheets as special cases, and we give some of their properties. We show that for certain values…

Probability · Mathematics 2008-12-01 Johanna Garzón

In this work we introduce correlated random walks on $\Z$. When picking suitably at random the coefficient of correlation, and taking the average over a large number of walks, we obtain a discrete Gaussian process, whose scaling limit is…

Probability · Mathematics 2007-05-23 Enriquez Nathanael

Fractional Brownian motion, a stochastic process with long-time correlations between its increments, is a prototypical model for anomalous diffusion. We analyze fractional Brownian motion in the presence of a reflecting wall by means of…

Statistical Mechanics · Physics 2018-02-21 Alexander H. O. Wada , Thomas Vojta

Someone knowledgeable in nonstandard analysis may get the feeling that in the nonlinear theory of generalized functions, too often one works directly on the nets and spends effort to obtain results that should be clear from general…

Functional Analysis · Mathematics 2011-02-01 Hans Vernaeve

Scattering moments provide nonparametric models of random processes with stationary increments. They are expected values of random variables computed with a nonexpansive operator, obtained by iteratively applying wavelet transforms and…

Methodology · Statistics 2015-03-17 Joan Bruna , Stéphane Mallat , Emmanuel Bacry , Jean-François Muzy

Field equations with time and coordinates derivatives of noninteger order are derived from stationary action principle for the cases of power-law memory function and long-range interaction in systems. The method is applied to obtain a…

Mathematical Physics · Physics 2015-03-11 Vasily E. Tarasov , George M. Zaslavsky

We introduce a simulation-based, amortised Bayesian inference scheme to infer the parameters of random walks. Our approach learns the posterior distribution of the walks' parameters with a likelihood-free method. In the first step a graph…

Machine Learning · Computer Science 2022-12-07 Hippolyte Verdier , François Laurent , Alhassan Cassé , Christian Vestergaard , Jean-Baptiste Masson

We consider the invariance principle without the classical condition of asymptotic negligibility of individual terms. More precisely, we explore the difference of the following two distributions in the space C (of continuous functions on…

Probability · Mathematics 2007-05-23 Youri Davydov , Vladimir Rotar

Uniform large deviation principles for positive functionals of all equivalent types of infinite dimensional Brownian motions acting together with a Poisson random measure are established. The core of our approach is a variational…

Probability · Mathematics 2014-03-13 Vasileios Maroulas

Fractional Brownian motion (FBM), a non-Markovian self-similar Gaussian stochastic process with long-ranged correlations, represents a widely applied, paradigmatic mathematical model of anomalous diffusion. We report the results of…

We study functional limit theorems for linear type processes with short memory under the assumption that the innovations are dependent identically distributed random variables with infinite variance and in the domain of attraction of stable…

Probability · Mathematics 2010-05-20 Marta Tyran-Kaminska

We prove the transfer principle for fractional Ornstein-Uhlenbeck processes, i.e., we construct a Brownian motion that has the same filtration as the fractional Ornstein-Uhlenbeck process and then represent the fractional Ornstein-Uhlenbeck…

Probability · Mathematics 2023-11-03 Tommi Sottinen , Lauri Viitasaari

The fractional non-homogeneous Poisson process was introduced by a time-change of the non-homogeneous Poisson process with the inverse $\alpha$-stable subordinator. We propose a similar definition for the (non-homogeneous) fractional…

Probability · Mathematics 2017-11-27 Nikolai Leonenko , Enrico Scalas , Mailan Trinh

A functional limit theorem for the empirical measure-valued process of eigenvalues of a matrix fractional Brownian motion is obtained. It is shown that the limiting measure-valued process is the non-commutative fractional Brownian motion…

Probability · Mathematics 2015-06-23 Juan Carlos Pardo , Victor Pérez-Abreu , José Luis Pérez-Garmendia

The generalized fractional Brownian motion is a Gaussian self-similar process whose increments are not necessarily stationary. It appears in applications as the scaling limit of a shot noise process with a power law shape function and…

Probability · Mathematics 2020-12-02 Tomoyuki Ichiba , Guodong Pang , Murad S. Taqqu

We focus on fast-slow systems involving both fractional Brownian motion (fBm) and standard Brownian motion (Bm). The integral with respect to Bm is the standard Ito integral, and the integral with respect to fBm is the generalised…

Dynamical Systems · Mathematics 2021-11-04 Bin Pei , Yuzuru Inahama , Yong Xu

We investigate a method for extracting nonlinear principal components (NPCs). These NPCs maximize variation subject to smoothness and orthogonality constraints; but we allow for a general class of constraints and multivariate probability…

Methodology · Statistics 2009-08-06 Xioahong Chen , Lars Peter Hansen , Jose Scheinkman

The paper is devoted to the existence of integral functionals $\int_0^\infty f(X(t))\,{\mathrm{d}t}$ for several classes of processes in $\mathbb{R}$ with $d\ge 3$. Some examples such as Brownian motion, fractional Brownian motion, compound…

Probability · Mathematics 2021-04-02 Yuri Kondratiev , Yuliya Mishura , José L. da Silva

We prove a general functional limit theorem for multiparameter fractional Brownian motion. The functional law of the iterated logarithm, functional L\'{e}vy's modulus of continuity and many other results are its particular cases.…

Probability · Mathematics 2013-11-18 Anatoliy Malyarenko

Fractional Brownian motion (fBm) is a canonical model for long-memory phenomena. In the presence of large amounts of potentially memory-bearing data, the data are often averaged, which can change the structure of the underlying…

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