We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensional small diffusions. Our test is based on discrete observation of the processes, and the diffusion coefficient is a nuisance function which is estimated in our testing procedure. We prove that the limit distribution of our test is the supremum of the standard Brownian motion, and thus our test is asymptotically distribution free. We also show that our test is consistent under any fixed alternatives
In this paper we propose the use of φ{symbol} - divergences as test statistics to verify simple hypo...
Abstract. We consider a one-dimensional diffusion process (Xt) which is observed at n + 1 discrete t...
31 pages, 2 figures, 2 tablesWe consider a multidimensional diffusion X with drift coefficient b({\a...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness-of-fit test problem for the drift coefficient of one-dimensiona...
We consider parametric hypotheses testing for multidimensional ergodic diffusion processes observed ...
In this paper we propose the use of $\phi$-divergences as test statistics to verify simple hypothese...
AbstractThe maximum likelihood estimation of the unknown parameter of a diffusion process based on a...
A nonparametric kernel estimator of the drift (diffusion) term in a diffusion model are developed gi...
A problem of goodness-of-fit test for ergodic diffusion processes is presented. In the null hypothes...
We consider a diffusion model of small variance type with positive drift function varying in a nonpa...
The maximum likelihood estimation of the unknown parameter of a diffusion process based on an approx...
We consider a model of small diffusion type where the function which governs the drift term varies i...
In this paper we propose the use of φ{symbol} - divergences as test statistics to verify simple hypo...
Abstract. We consider a one-dimensional diffusion process (Xt) which is observed at n + 1 discrete t...
31 pages, 2 figures, 2 tablesWe consider a multidimensional diffusion X with drift coefficient b({\a...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness of fit test problem for the drift coefficient of one-dimensiona...
We consider a nonparametric goodness-of-fit test problem for the drift coefficient of one-dimensiona...
We consider parametric hypotheses testing for multidimensional ergodic diffusion processes observed ...
In this paper we propose the use of $\phi$-divergences as test statistics to verify simple hypothese...
AbstractThe maximum likelihood estimation of the unknown parameter of a diffusion process based on a...
A nonparametric kernel estimator of the drift (diffusion) term in a diffusion model are developed gi...
A problem of goodness-of-fit test for ergodic diffusion processes is presented. In the null hypothes...
We consider a diffusion model of small variance type with positive drift function varying in a nonpa...
The maximum likelihood estimation of the unknown parameter of a diffusion process based on an approx...
We consider a model of small diffusion type where the function which governs the drift term varies i...
In this paper we propose the use of φ{symbol} - divergences as test statistics to verify simple hypo...
Abstract. We consider a one-dimensional diffusion process (Xt) which is observed at n + 1 discrete t...
31 pages, 2 figures, 2 tablesWe consider a multidimensional diffusion X with drift coefficient b({\a...