Hermite processes are self-similar processes with stationary increments which appear as limits of normalized sums of random variables with long range dependence. The Hermite process of order 1 is fractional Brownian motion and the Hermite process of order 2 is the Rosenblatt process. We consider here the sum of two Hermite processes of orders and and of different Hurst parameters. We then study its quadratic variations at different scales. This is akin to a wavelet decomposition. We study both the cases where the Hermite processes are dependent and where they are independent. In the dependent case, we show that the quadratic variation, suitably normalized, converges either to a normal or to a Rosenblatt distribution, whatever the order of...
We consider stationary processes with long memory which are non-Gaussian and represented as Hermite ...
We study the limit law of a vector made up of normalized sums of functions of long-range dependent s...
This thesis focuses on an analytical and statistical study of stochastic differential equations (SDE...
International audienceHermite processes are self--similar processes with stationary increments which...
We analyze the asymptotic behavior of quadratic variations for a class of non-Gaussian self-similar ...
Let Zt q,H t∈[0,1]d denote a d-parameter Hermite random field of order q ≥ 1 and self-simila...
International audienceUsing multiple stochastic integrals and the Malliavin calculus, we analyze the...
To appear in "Theory of Probability and its Applications"International audienceBy using multiple Wie...
International audienceUsing multiple Wiener-Itô stochastic integrals and Malliavin calculus we study...
Wavelet-type random series representations of the well-known Fractional Brownian Motion (FBM) and m...
We define multifractional Hermite processes which generalize and extend both multifractional Browni...
12 pagesLet $q\geq 2$ be a positive integer, $B$ be a fractional Brownian motion with Hurst index $H...
We introduce a broad class of self-similar processes \{Z(t),t\ge 0\} called generalized Hermite proc...
International audienceBy using chaos expansion into multiple stochastic integrals, we make a wavelet...
This thesis consists of two parts. Part I is an introduction to Hermite processes, Hermite random fie...
We consider stationary processes with long memory which are non-Gaussian and represented as Hermite ...
We study the limit law of a vector made up of normalized sums of functions of long-range dependent s...
This thesis focuses on an analytical and statistical study of stochastic differential equations (SDE...
International audienceHermite processes are self--similar processes with stationary increments which...
We analyze the asymptotic behavior of quadratic variations for a class of non-Gaussian self-similar ...
Let Zt q,H t∈[0,1]d denote a d-parameter Hermite random field of order q ≥ 1 and self-simila...
International audienceUsing multiple stochastic integrals and the Malliavin calculus, we analyze the...
To appear in "Theory of Probability and its Applications"International audienceBy using multiple Wie...
International audienceUsing multiple Wiener-Itô stochastic integrals and Malliavin calculus we study...
Wavelet-type random series representations of the well-known Fractional Brownian Motion (FBM) and m...
We define multifractional Hermite processes which generalize and extend both multifractional Browni...
12 pagesLet $q\geq 2$ be a positive integer, $B$ be a fractional Brownian motion with Hurst index $H...
We introduce a broad class of self-similar processes \{Z(t),t\ge 0\} called generalized Hermite proc...
International audienceBy using chaos expansion into multiple stochastic integrals, we make a wavelet...
This thesis consists of two parts. Part I is an introduction to Hermite processes, Hermite random fie...
We consider stationary processes with long memory which are non-Gaussian and represented as Hermite ...
We study the limit law of a vector made up of normalized sums of functions of long-range dependent s...
This thesis focuses on an analytical and statistical study of stochastic differential equations (SDE...