AbstractBy means of the Malliavin Calculus, we derive asymptotic expansion of the probability distributions of statistics for systems perturbed by small noises. These results are applied to the problem of the second order asymptotic efficiency of the maximum likelihood estimator
maximum likelihood estimator, asymptotic efficiency, stochastic partial differential equations,
International audienceUsing multiple Wiener-Itô stochastic integrals and Malliavin calculus we study...
The objective of this work is to provide numerical simulations in support of a collection of existin...
By means of the Malliavin Calculus, we derive asymptotic expansion of the probability distributions ...
AbstractBy means of the Malliavin calculus, we present an expansion formula for the distribution of ...
By combining the Malliavin calculus with Fourier techniques, we develop a high-order asymptotic expa...
In this dissertation we present several applications of Malliavin calculus, both to the statistical ...
AbstractSuppose on a probability space (Ω, F, P), a partially observable random process (xt, yt), t ...
In this article, we study the hyperbolic Anderson model driven by a space-time colored Gaussian homo...
AbstractIt is shown that the probability that a suitably standardized asymptotic maximum likelihood ...
The maximum likelihood estimator (MLE) of the fractional difference parameter in the Gaussian ARFIMA(...
In this paper I derive the asymptotics of the exact, Euler, and Milstein ML estimators for diffusion...
This thesis is primarily concerned with the investigation of asymptotic properties of the maximum l...
Suppose on a probability space ([Omega], F, P), a partially observable random process (xt, yt), t >=...
AbstractWe consider a family of sets {As,s≥0} on the Wiener space whose boundary only satisfies smoo...
maximum likelihood estimator, asymptotic efficiency, stochastic partial differential equations,
International audienceUsing multiple Wiener-Itô stochastic integrals and Malliavin calculus we study...
The objective of this work is to provide numerical simulations in support of a collection of existin...
By means of the Malliavin Calculus, we derive asymptotic expansion of the probability distributions ...
AbstractBy means of the Malliavin calculus, we present an expansion formula for the distribution of ...
By combining the Malliavin calculus with Fourier techniques, we develop a high-order asymptotic expa...
In this dissertation we present several applications of Malliavin calculus, both to the statistical ...
AbstractSuppose on a probability space (Ω, F, P), a partially observable random process (xt, yt), t ...
In this article, we study the hyperbolic Anderson model driven by a space-time colored Gaussian homo...
AbstractIt is shown that the probability that a suitably standardized asymptotic maximum likelihood ...
The maximum likelihood estimator (MLE) of the fractional difference parameter in the Gaussian ARFIMA(...
In this paper I derive the asymptotics of the exact, Euler, and Milstein ML estimators for diffusion...
This thesis is primarily concerned with the investigation of asymptotic properties of the maximum l...
Suppose on a probability space ([Omega], F, P), a partially observable random process (xt, yt), t >=...
AbstractWe consider a family of sets {As,s≥0} on the Wiener space whose boundary only satisfies smoo...
maximum likelihood estimator, asymptotic efficiency, stochastic partial differential equations,
International audienceUsing multiple Wiener-Itô stochastic integrals and Malliavin calculus we study...
The objective of this work is to provide numerical simulations in support of a collection of existin...
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