In this paper we study the fractional Brownian motion (FBM) time changed by the inverse Gaussian (IG) process and its inverse, called the inverse to the inverse Gaussian (IIG) process. Some properties of the time-changed processes are similar to those of the classical FBM, such as long-range dependence. However, one can also observe different characteristics that are not satisfied by the FBM. We study the distributional properties of both subordinators, namely, IG and IIG processes, and also that of the FBM time changed by these subordinators. We establish also the connections between the subordinated processes considered and the continuous-time random-walk model. For the application part, we introduce the simulation procedures for both pro...
We start by defining a subordinator by means of the lower-incomplete gamma function. This can be con...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
International audienceThe use of diffusion models driven by fractional noise has become popular for ...
A fractional normal inverse Gaussian (FNIG) process is a fractional Brownian motion subordinated to ...
We revisit an inverse first-passage time (IFPT) problem, in the cases of fractional Brownian motion...
The first-exit time process of an inverse Gaussian Levy process is considered. The one-dimensional d...
Abstract. A Brownian time process is a Markov process subordinated to the absolute value of an indep...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
In the paper, we consider the problem of simulation of a strictly ?-sub-Gaussian generalized fractio...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
Brownian motion can be characterized as a generalized random process and, as such, has a generalized...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (su...
We consider some time-changed diffusion processes obtained by applying the Doob transformation rule ...
We start by defining a subordinator by means of the lower-incomplete gamma function. This can be con...
We start by defining a subordinator by means of the lower-incomplete gamma function. This can be con...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
International audienceThe use of diffusion models driven by fractional noise has become popular for ...
A fractional normal inverse Gaussian (FNIG) process is a fractional Brownian motion subordinated to ...
We revisit an inverse first-passage time (IFPT) problem, in the cases of fractional Brownian motion...
The first-exit time process of an inverse Gaussian Levy process is considered. The one-dimensional d...
Abstract. A Brownian time process is a Markov process subordinated to the absolute value of an indep...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
In the paper, we consider the problem of simulation of a strictly ?-sub-Gaussian generalized fractio...
We investigate the main statistical parameters of the integral over time of the fractional Brownian ...
Brownian motion can be characterized as a generalized random process and, as such, has a generalized...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
We study a long-range dependence Gaussian process which we call “sub-fractional Brownian motion” (su...
We consider some time-changed diffusion processes obtained by applying the Doob transformation rule ...
We start by defining a subordinator by means of the lower-incomplete gamma function. This can be con...
We start by defining a subordinator by means of the lower-incomplete gamma function. This can be con...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
International audienceThe use of diffusion models driven by fractional noise has become popular for ...