We study a family of stationary increment Gaussian processes, indexed by time. These processes are determined by certain measures σ (generalized spectral measures), and our focus here is on the case when the measure σ is a singular measure. We characterize the processes arising from when σ is in one of the classes of affine self-similar measures. Our analysis makes use of Kondratiev-white noise spaces. With the use of a priori estimates and the Wick calculus, we extend and sharpen (see Theorem 7.1) earlier computations of Ito stochastic integration developed for the special case of stationary increment processes having absolutely continuous measures. We further obtain an associated Ito formula (see Theorem 8.1)
In this paper we present a general mathematical construction that allows us to define a parametric ...
A recurrent theme in functional analysis is the interplay between the theory of positive definite fu...
The aim of this work is to define and perform a study of local times of all Gaussian processes that ...
AbstractWe study a family of stationary increment Gaussian processes, indexed by time. These process...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
Using the white noise space framework, we construct and study a class of Gaussian processes with sta...
International audienceStochastic integration with respect to Gaussian processes has raised strong in...
In this paper we study a general family of multivariable Gaussian stochastic processes. Each process...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
Given a Gaussian stationary increment processes, we show that a Skorokhod-Hitsuda stochastic integra...
Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, m...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
In this paper we present a general mathematical construction that allows us to define a parametric ...
A recurrent theme in functional analysis is the interplay between the theory of positive definite fu...
The aim of this work is to define and perform a study of local times of all Gaussian processes that ...
AbstractWe study a family of stationary increment Gaussian processes, indexed by time. These process...
AbstractUsing the white noise space framework, we construct and study a class of Gaussian processes ...
Tyt. z nagłówka.Bibliogr. s. 415-416.Given a Gaussian stationary increment processes, we show that a...
Using the white noise space framework, we construct and study a class of Gaussian processes with sta...
International audienceStochastic integration with respect to Gaussian processes has raised strong in...
In this paper we study a general family of multivariable Gaussian stochastic processes. Each process...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
Stochastic integration with respect to Gaussian processes, such as fractional Brownian motion (fBm) ...
Given a Gaussian stationary increment processes, we show that a Skorokhod-Hitsuda stochastic integra...
Stochastic integration \textit{wrt} Gaussian processes has raised strong interest in recent years, m...
We develop a stochastic analysis for a Gaussian process $X$ with singular covariance by an intrinsic...
Using the white noise space setting, we define and study stochastic integrals with respect to a clas...
In this paper we present a general mathematical construction that allows us to define a parametric ...
A recurrent theme in functional analysis is the interplay between the theory of positive definite fu...
The aim of this work is to define and perform a study of local times of all Gaussian processes that ...