In this paper, we investigate the representation of a class of non-Gaussian processes, namely generalized grey Brownian motion, in terms of a weighted integral of a stochastic process which is a solution of a certain stochastic differential equation. In particular, the underlying process can be seen as a non-Gaussian extension of the Ornstein–Uhlenbeck process, hence generalizing the representation results of Muravlev, Russian Math. Surveys 66 (2), 2011 as well as Harms and Stefanovits, Stochastic Process. Appl. 129, 2019 to the non-Gaussian case.
The stochastic integral representation for an arbitrary random variable in a standard $L_2$-space is...
Stochastic Integrals Driven by Isonormal Gaussian Processes and Applications Master Thesis - Petr Čo...
This volume presents recent developments in the area of Lévy-type processes and more general stochas...
In this paper, we investigate the potential for a class of non-Gaussian processes so-called generali...
We show that every separable Gaussian process with integrable variance function admits a Fredholm re...
On the problem of stochastic integral representations of functions of the Brownian motion I
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
We consider an ensemble of Ornstein-Uhlenbeck processes featuring a population of relaxation times a...
Brownian motion can be characterized as a generalized random process and, as such, has a generalized...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We develop a notion of nonlinear expectation-G-expectation-generated by a nonlinear heat equation wi...
AbstractWe study the simulation of stochastic processes defined as stochastic integrals with respect...
A novel representation of functions, called generalized Taylor form, is applied to the filtering of ...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
The stochastic integral representation for an arbitrary random variable in a standard $L_2$-space is...
Stochastic Integrals Driven by Isonormal Gaussian Processes and Applications Master Thesis - Petr Čo...
This volume presents recent developments in the area of Lévy-type processes and more general stochas...
In this paper, we investigate the potential for a class of non-Gaussian processes so-called generali...
We show that every separable Gaussian process with integrable variance function admits a Fredholm re...
On the problem of stochastic integral representations of functions of the Brownian motion I
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
We consider an ensemble of Ornstein-Uhlenbeck processes featuring a population of relaxation times a...
Brownian motion can be characterized as a generalized random process and, as such, has a generalized...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
In recent years there have been many publications studying dynamic systems subjected to non-Gaussian...
We develop a notion of nonlinear expectation-G-expectation-generated by a nonlinear heat equation wi...
AbstractWe study the simulation of stochastic processes defined as stochastic integrals with respect...
A novel representation of functions, called generalized Taylor form, is applied to the filtering of ...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
The stochastic integral representation for an arbitrary random variable in a standard $L_2$-space is...
Stochastic Integrals Driven by Isonormal Gaussian Processes and Applications Master Thesis - Petr Čo...
This volume presents recent developments in the area of Lévy-type processes and more general stochas...