We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation being subject to a measurement error. All errors are independent and centered Gaussian with known variance pn. There is an unknown parameter to estimate within the diffusion coefficient. In this second paper we construct estimators which are asymptotically optimal when the process X is a Gaussian martingale, and we conjecture that they are also optimal in the general case
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
AbstractThe maximum likelihood estimation of the unknown parameter of a diffusion process based on a...
Diffusion models observed with noise are widely used in biology and in finance, to take into account...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
Abstract. We consider a diusion process X which is observed at times i=n for i = 0; 1; : : : ; n, ea...
Abstract. We consider a diusion process X which is observed at times i=n for i = 0; 1; : : : ; n, ea...
: A new type of martingale estimating function is proposed for inference about classes of diffusion ...
In this article, general estimating functions for ergodic diffusions sam-pled at high frequency with...
Parametric estimation for diffusion processes is considered for high frequency ob-servations over a ...
We consider the problem of the estimation of the invariant distribution function of an ergodic diffu...
We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonran...
We study the estimation problem for a continuous (Gaussian) process with independent increments when...
In this paper, the Prediction-Based Estimating Functions proposed by Sørensen (1999) are generalized...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
AbstractThe maximum likelihood estimation of the unknown parameter of a diffusion process based on a...
Diffusion models observed with noise are widely used in biology and in finance, to take into account...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
We consider a diffusion process X which is observed at times i/n for i = 0,1,...,n, each observation...
Abstract. We consider a diusion process X which is observed at times i=n for i = 0; 1; : : : ; n, ea...
Abstract. We consider a diusion process X which is observed at times i=n for i = 0; 1; : : : ; n, ea...
: A new type of martingale estimating function is proposed for inference about classes of diffusion ...
In this article, general estimating functions for ergodic diffusions sam-pled at high frequency with...
Parametric estimation for diffusion processes is considered for high frequency ob-servations over a ...
We consider the problem of the estimation of the invariant distribution function of an ergodic diffu...
We study maximum-likelihood-type estimation for diffusion processes when the coefficients are nonran...
We study the estimation problem for a continuous (Gaussian) process with independent increments when...
In this paper, the Prediction-Based Estimating Functions proposed by Sørensen (1999) are generalized...
This thesis is composed of two parts. The first part is devoted to inference for discretely observed...
AbstractThe maximum likelihood estimation of the unknown parameter of a diffusion process based on a...
Diffusion models observed with noise are widely used in biology and in finance, to take into account...