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The process $(G_t)_{t\in[0,T]}$ is referred to as a fractional Gaussian process if the first-order partial derivative of the difference between its covariance function and that of the fractional Brownian motion $(B^H_t)_{t\in[0,T ]}$ is a…

Probability · Mathematics 2023-09-20 Yong Chen , Ying Li

The trace of a Markov process is the time changed process of the original process on the support of the Revuz measure used in the time change. In this paper, we will concentrate on the reflecting Brownian motions on certain closed strips.…

Probability · Mathematics 2021-09-08 Liping Li , Wenjie Sun

We prove that a set-indexed process is a set-indexed fractional Brownian motion if and only if its projections on all the increasing paths are one-parameter time changed fractional Brownian motions. As an application, we present an integral…

Probability · Mathematics 2007-05-23 Erick Herbin , Ely Merzbach

In this paper we study the integral of the supremum process of standard Brownian motion. We present an explicit formula for the moments of the integral (or area) A(T), covered by the process in the time interval [0,T]. The Laplace transform…

Probability · Mathematics 2007-07-09 Svante Janson , Niclas Petersson

We introduce a new Gaussian process, a generalization of both fractional and subfractional Brownian motions, which could serve as a good model for a larger class of natural phenomena. We study its main stochastic properties and some…

Probability · Mathematics 2017-04-10 Mounir Zili

We investigate the stochastic processes obtained as the fractional Riemann-Liouville integral of order $\alpha \in (0,1)$ of Gauss-Markov processes. The general expressions of the mean, variance and covariance functions are given. Due to…

Probability · Mathematics 2019-05-21 Mario Abundo , Enrica Pirozzi

We consider certain questions pertaining to noncommutative generalized Brownian motions with multiple processes. We establish a framework for generalized Brownian motion with multiple processes similar to that defined by Guta and prove…

Operator Algebras · Mathematics 2015-04-10 Adam Merberg

Motivated by the dynamics of resonant neurons we consider a differentiable, non-Markovian random process $x(t)$ and particularly the time after which it will reach a certain level $x_b$. The probability density of this first passage time is…

Statistical Mechanics · Physics 2009-11-11 T. Verechtchaguina , I. M. Sokolov , L. Schimansky-Geier

We study pointwise estimation and uncertainty quantification for a sparse variational Gaussian process method with eigenvector inducing variables. For a rescaled Brownian motion prior, we derive theoretical guarantees and limitations for…

Statistics Theory · Mathematics 2023-11-01 Luke Travis , Kolyan Ray

We show that if a random variable is a final value of an adapted Holder continuous process, then it can be represented as a stochastic integral with respect to fractional Brownian motion, and the integrand is an adapted process, continuous…

Probability · Mathematics 2014-03-11 Georgiy Shevchenko , Lauri Viitasaari

We show that if a random variable is the final value of an adapted log-H\"{o}lder continuous process, then it can be represented as a stochastic integral with respect to a fractional Brownian motion with adapted integrand. In order to…

Probability · Mathematics 2015-10-08 Taras Shalaiko , Georgiy Shevchenko

We investigate the process of eigenvalues of a symmetric matrix-valued process which upper diagonal entries are independent one-dimensional H\"older continuous Gaussian processes of order gamma in (1/2,1). Using the stochastic calculus with…

Probability · Mathematics 2014-07-29 David Nualart , Victor Pérez-Abreu

We study integral representations of random variables with respect to general H\"older continuous processes and with respect to two particular cases; fractional Brownian motion and mixed fractional Brownian motion. We prove that arbitrary…

Probability · Mathematics 2014-05-01 Georgiy Shevchenko , Lauri Viitasaari

Suppose a solid has a crack filled with a gas. If the crack reaches the surrounding medium, how long does it take the gas to diffuse out of the crack? Iterated Brownian motion serves as a model for diffusion in a crack. If \tau is the first…

Probability · Mathematics 2007-05-23 R. Dante DeBlassie

The paper is devoted to the integral functionals $\int_0^\infty f(X_t)\,{\mathrm{d}t}$ of Markov processes in $\X$ in the case $d\ge 3$. It is established that such functionals can be presented as the integrals $\int_{\X} f(y) \G(x,…

Probability · Mathematics 2022-07-20 Yuri Kondratiev , José L. da Silva

This paper is the first part of our survey on various results about the distribution of exponential type Brownian functionals defined as an integral over time of geometric Brownian motion. Several related topics are also mentioned.

Probability · Mathematics 2007-05-23 Hiroyuki Matsumoto , Marc Yor

This paper is concerned with the study of the embedding circulant matrix method to simulate stationary complex-valued Gaussian sequences. The method is, in particular, shown to be well-suited to generate circularly-symmetric stationary…

Statistics Theory · Mathematics 2016-04-04 Jean-Francois Coeurjolly , Emilio Porcu

Under the framework of G-expectation and G-Brownian motion, we introduce It\^o's integral for stochastic processes without assuming quasi-continuity. Then we can obtain It\^o's integral on stopping time interval. This new formulation…

Probability · Mathematics 2011-04-07 Xinpeng Li , Shige Peng

In this paper, we are concerned with the large N limit of linear combinations of the entries of a Brownian motion on the group of N by N unitary matrices. We prove that the process of such a linear combination converges to a Gaussian one.…

Probability · Mathematics 2011-06-22 Florent Benaych-Georges

The first passage time problem for Brownian motions hitting a barrier has been extensively studied in the literature. In particular, many incarnations of integral equations which link the density of the hitting time to the equation for the…

Probability · Mathematics 2009-02-24 Sebastian Jaimungal , Alex Kreinin , Angelo Valov