International audienceFollowing recent works from Lavancier et. al., we study the covariance structure of the multivariate fractional Gaussian noise. We evaluate several parameters of the model that allow to control the correlation structure at lag zero between all the components of the multivariate process. Then, we specify an algorithm that allows the exact simulation of multivariate fractional Gaussian noises and thus fractional Brownian motions. Illustrations involve the estimation of the Hurst exponents of each of the components
International audienceMultifractional Brownian motion (mBm) was introduced to overcome certain limit...
International audienceIn the modern world of "Big Data," dynamic signals are often multivariate and ...
Fractional Brownian motion (FBM) with Hurst parameter index between 0 and 1 is a stochastic process ...
International audienceThis paper deals with the identification of the multivariate fractional Browni...
http://smf4.emath.fr/Publications/SeminairesCongres/2013/28/html/smf_sem-cong_28_65-87.phpInternatio...
International audienceSince the pioneering work by Mandelbrot and Van Ness in 1968, the fractional B...
In this study, we first discretize the fractional Brownian motion in time and observe multivariate G...
International audienceA generalization of fractional Brownian motion (fBm) of parameter H in ]0, 1[ ...
The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm) has been widely used fo...
In this study, we mainly propose an algorithm to generate correlated random walk converging to fract...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
The application of fractional Brownian Motion (fBm) has drawn a lot of attention in a large number o...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
We investigate the stochastic processes obtained as the fractional Riemann-Liouville inte-gral of or...
<p>Representation of the continuum of fractal processes, with: the two families of fractional Gaussi...
International audienceMultifractional Brownian motion (mBm) was introduced to overcome certain limit...
International audienceIn the modern world of "Big Data," dynamic signals are often multivariate and ...
Fractional Brownian motion (FBM) with Hurst parameter index between 0 and 1 is a stochastic process ...
International audienceThis paper deals with the identification of the multivariate fractional Browni...
http://smf4.emath.fr/Publications/SeminairesCongres/2013/28/html/smf_sem-cong_28_65-87.phpInternatio...
International audienceSince the pioneering work by Mandelbrot and Van Ness in 1968, the fractional B...
In this study, we first discretize the fractional Brownian motion in time and observe multivariate G...
International audienceA generalization of fractional Brownian motion (fBm) of parameter H in ]0, 1[ ...
The fractional Gaussian noise/fractional Brownian motion framework (fGn/fBm) has been widely used fo...
In this study, we mainly propose an algorithm to generate correlated random walk converging to fract...
Fractional Brownian motion is a nontrivial generalization of standard Brownian motion (Wie- ner proc...
The application of fractional Brownian Motion (fBm) has drawn a lot of attention in a large number o...
This article focuses on simulating fractional Brownian motion (fBm). Despite the availability of sev...
We investigate the stochastic processes obtained as the fractional Riemann-Liouville inte-gral of or...
<p>Representation of the continuum of fractal processes, with: the two families of fractional Gaussi...
International audienceMultifractional Brownian motion (mBm) was introduced to overcome certain limit...
International audienceIn the modern world of "Big Data," dynamic signals are often multivariate and ...
Fractional Brownian motion (FBM) with Hurst parameter index between 0 and 1 is a stochastic process ...