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Within the past two decades, Gaussian process regression has been increasingly used for modeling dynamical systems due to some beneficial properties such as the bias variance trade-off and the strong connection to Bayesian mathematics. As…

Systems and Control · Electrical Eng. & Systems 2021-02-11 Thomas Beckers

We find the exact winding number distribution of Riemann-Liouville fractional Brownian motion for large times in two dimensions using the propagator of a free particle. The distribution is similar to the Brownian motion case and it is of…

Statistical Mechanics · Physics 2009-11-13 M. A. Rajabpour

In this note, we introduce the notion of $\alpha$-IDT processes which is obtained from a slight and fundamental modification of the IDT property. Several examples of $\alpha$-IDT processes are given and Gaussian processes which are…

Probability · Mathematics 2012-10-17 Antoine Hakassou , Youssef Ouknine

We introduce an extended version of the fractional Ornstein-Uhlenbeck (FOU) process where the integrand is replaced by the exponential of an independent L\'evy process. We call the process the generalized fractional Ornstein-Uhlenbeck…

Probability · Mathematics 2008-07-15 Kotaro Endo , Muneya Matsui

This paper introduces a general and new formalism to model the turbulent wave-front phase using fractional Brownian motion processes. Moreover, it extends results to non-Kolmogorov turbulence. In particular, generalized expressions for the…

Atmospheric and Oceanic Physics · Physics 2015-06-26 Dario G. Perez , Luciano Zunino , Mario Garavaglia

A simple variogram model with two parameters is presented that includes the power variogram for the fractional Brownian motion, a modified De Wijsian model, the generalized Cauchy model and the multiquadrics model. One parameter controls…

Methodology · Statistics 2014-12-08 Martin Schlather

The multivariate Ornstein-Uhlenbeck process is used in many branches of science and engineering to describe the regression of a system to its stationary mean. Here we present an $O(N)$ Bayesian method to estimate the drift and diffusion…

Statistical Mechanics · Physics 2018-08-01 Rajesh Singh , Dipanjan Ghosh , R. Adhikari

In this paper, we rely on the additive decomposition in law satisfied by a class of stochastic processes, combined with the well-known regulariy properties of fractional Brownian motion, to establish Besov-Orlicz regularity of their sample…

Probability · Mathematics 2026-05-11 Rachid Belfadli , Brahim Boufoussi , Youssef Ouknine

Eigenproblems frequently arise in theory and applications of stochastic processes, but only a few have explicit solutions. Those which do, are usually solved by reduction to the generalized Sturm--Liouville theory for differential…

Probability · Mathematics 2018-03-06 P. Chigansky , M. Kleptsyna , D. Marushkevych

We consider two independent Gaussian processes that admit a representation in terms of a stochastic integral of a deterministic kernel with respect to a standard Wiener process. In this paper we construct two families of processes, from a…

Probability · Mathematics 2009-09-02 Xavier Bardina , David Bascompte

We propose an approach to compute the boundary crossing probabilities for a class of diffusion processes which can be expressed as piecewise monotone (not necessarily one-to-one) functionals of a standard Brownian motion. This class…

Probability · Mathematics 2007-05-23 Liqun Wang , Klaus Pötzelberger

We study well-posedness of sweeping processes with stochastic perturbations generated by a fractional Brownian motion and convergence of associated numerical schemes. To this end, we first prove new existence, uniqueness and approximation…

Classical Analysis and ODEs · Mathematics 2015-05-07 Adrian Falkowski , Leszek Slominski

Fractional Brownian motion can be represented as an integral of a deterministic kernel w.r.t. an ordinary Brownian motion either on infinite or compact interval. In previous literature fractional L\'evy processes are defined by integrating…

Probability · Mathematics 2011-11-11 Heikki Tikanmäki , Yuliya Mishura

In this paper, we consider an inference problem for an Ornstein-Uhlenbeck process driven by a general one-dimensional centered Gaussian process $(G_t)_{t\ge 0}$. The second order mixed partial derivative of the covariance function $ R(t,\,…

Probability · Mathematics 2020-02-25 Yong Chen , Hongjuan Zhou

We prove that we can identify three types of pointwise behaviour in the regularity of the (generalized) Rosenblatt process. This extends to a non Gaussian setting previous results known for the (fractional) Brownian motion. On this purpose,…

Probability · Mathematics 2022-03-17 Lara Daw , Laurent Loosveldt

Fractional calculus has been used to describe physical systems with complexity. Here, we show that a fractional calculus approach can restore or include complexity in any physical systems that can be described by partial differential…

Mesoscale and Nanoscale Physics · Physics 2024-08-06 Kyle Rockwell , Ezio Iacocca

We construct a new process using a fractional Brownian motion and a fractional Ornstein-Uhlenbeck process of the Second Kind as building blocks. We consider the increments of the new process in discrete time and, as a result, we obtain a…

Mathematical Finance · Quantitative Finance 2017-12-11 José Igor Morlanes

Bifractional Brownian motion (bfBm) is a centered Gaussian process with covariance \[ R^{(H,K)}(s,t)= 2^{-K} \left( \left(|s|^{2H}+|t|^{2H} \right)^{K}-|t-s|^{2HK}\right), \qquad s,t\in R. \] We study the existence of bfBm for a given pair…

Probability · Mathematics 2019-07-04 Mikhail Lifshits , Ksenia Volkova

A stochastic calculus is given for processes described by stochastic integrals with respect to fractional Brownian motions and Rosenblatt processes somewhat analogous to the stochastic calculus for It\^{o} processes. These processes for…

Probability · Mathematics 2019-08-02 Petr Čoupek , Tyrone E. Duncan , Bozenna Pasik-Duncan

The goal of this communication is to propose a generalized notion of the "traditional derivative". This generalization includes the fractional derivatives such as the Riemann-Liouville, Gruenwald-Letnikov, Weyl, Riesz, Caputo, Marchaud…

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