International audienceBesides fractional Brownian motion most non-Gaussian fractional fields are obtained by integration of deterministic kernels with respect to a random infinitely divisible measure. In this paper, generalized shot noise series are used to obtain approximations of most of these fractional fields, including linear and harmonizable fractional stable fields. Almost sure and $L^r$-norm rates of convergence, relying on asymptotic developments of the deterministic kernels, are presented as a consequence of an approximation result concerning series of symmetric random variables. When the control measure is infinite, normal approximation has to be used as a complement. The general framework is illustrated by simulations of classic...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
We study the approximation of stochastic differential equations driven by a fractional Brownian moti...
AbstractWe study the approximation of stochastic differential equations driven by a fractional Brown...
AbstractBesides fractional Brownian motion most non-Gaussian fractional fields are obtained by integ...
Besides fractional Brownian motion most non-Gaussian fractional fields are obtained by in-tegration ...
In the paper, we consider the problem of simulation of a strictly ?-sub-Gaussian generalized fractio...
In this study, we first discretize the fractional Brownian motion in time and observe multivariate G...
We discuss a family of random fields indexed by a parameter s ∈ R which we call the fractional Gauss...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
In this paper, we simulate sample paths of a class of symmetric α-stable processes using their serie...
International audienceTo simulate Gaussian fields poses serious numerical problems: storage and comp...
We explore a generalisation of the L´evy fractional Brownian field on the Euclidean space based on ...
We discuss a family of random fields indexed by a parameter s ∈ Rwhich we call the fractional Gaussi...
International audienceFollowing recent works from Lavancier et. al., we study the covariance structu...
To simulate Gaussian fields poses serious numerical problems: storage and computing time. The midpoi...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
We study the approximation of stochastic differential equations driven by a fractional Brownian moti...
AbstractWe study the approximation of stochastic differential equations driven by a fractional Brown...
AbstractBesides fractional Brownian motion most non-Gaussian fractional fields are obtained by integ...
Besides fractional Brownian motion most non-Gaussian fractional fields are obtained by in-tegration ...
In the paper, we consider the problem of simulation of a strictly ?-sub-Gaussian generalized fractio...
In this study, we first discretize the fractional Brownian motion in time and observe multivariate G...
We discuss a family of random fields indexed by a parameter s ∈ R which we call the fractional Gauss...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
In this paper, we simulate sample paths of a class of symmetric α-stable processes using their serie...
International audienceTo simulate Gaussian fields poses serious numerical problems: storage and comp...
We explore a generalisation of the L´evy fractional Brownian field on the Euclidean space based on ...
We discuss a family of random fields indexed by a parameter s ∈ Rwhich we call the fractional Gaussi...
International audienceFollowing recent works from Lavancier et. al., we study the covariance structu...
To simulate Gaussian fields poses serious numerical problems: storage and computing time. The midpoi...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
We study the approximation of stochastic differential equations driven by a fractional Brownian moti...
AbstractWe study the approximation of stochastic differential equations driven by a fractional Brown...