Add to ORKGWe apply Grenander’s method of sieves to the problem of identification or estimation of the ”drift ” function for linear stochastic systems driven by a fractional Brownian motion (fBm). We use an increasing sequence of finite dimensional subspaces of the parameter space as the natural sieves on which we maximise the likelihood function
Stochastic analysis with respect to fractional Brownian motion. Fractional Brownian motion (fBM for ...
We consider the problem of Hurst index estimation for solutions of stochastic differential equations...
summary:We solve the one-dimensional stochastic heat equation driven by fractional Brownian motion u...
We apply Grenander's method of sieves to the problem of identification or estimation of the "drift" ...
Introduction to fractional brownian calculus is pre-sented. Very recent advances in development of t...
We investigate the asymptotic properties of the maximum likelihood estimator and Bayes estimator of ...
We consider the problem of maximum likelihood estimation of the common trend parameter for a linear ...
We investigate ∈-upper and lower class functions for the maximum likelihood estimator of the d...
We apply the techniques of stochastic integration with respect to the frac-tional Brownian motion an...
In this paper we develop sensitivity analyses w.r.t. the long-range/memory noise parameter for solut...
Abstract: We present a non exhaustive bibliographical and comparative study of the problem of sim-ul...
International audienceWe apply the techniques of stochastic integration with respect to the fraction...
Self-similar stochastic processes are used for stochastic modeling whenever it is expected that long...
This book is devoted to a number of stochastic models that display scale invariance. It primarily fo...
International audienceWe present a non exhaustive bibliographical and comparative study of the probl...
Stochastic analysis with respect to fractional Brownian motion. Fractional Brownian motion (fBM for ...
We consider the problem of Hurst index estimation for solutions of stochastic differential equations...
summary:We solve the one-dimensional stochastic heat equation driven by fractional Brownian motion u...
We apply Grenander's method of sieves to the problem of identification or estimation of the "drift" ...
Introduction to fractional brownian calculus is pre-sented. Very recent advances in development of t...
We investigate the asymptotic properties of the maximum likelihood estimator and Bayes estimator of ...
We consider the problem of maximum likelihood estimation of the common trend parameter for a linear ...
We investigate ∈-upper and lower class functions for the maximum likelihood estimator of the d...
We apply the techniques of stochastic integration with respect to the frac-tional Brownian motion an...
In this paper we develop sensitivity analyses w.r.t. the long-range/memory noise parameter for solut...
Abstract: We present a non exhaustive bibliographical and comparative study of the problem of sim-ul...
International audienceWe apply the techniques of stochastic integration with respect to the fraction...
Self-similar stochastic processes are used for stochastic modeling whenever it is expected that long...
This book is devoted to a number of stochastic models that display scale invariance. It primarily fo...
International audienceWe present a non exhaustive bibliographical and comparative study of the probl...
Stochastic analysis with respect to fractional Brownian motion. Fractional Brownian motion (fBM for ...
We consider the problem of Hurst index estimation for solutions of stochastic differential equations...
summary:We solve the one-dimensional stochastic heat equation driven by fractional Brownian motion u...
