We consider a diffusion process which is observed at times for , each observation being subject to a measurement error. All errors are independent and centered gaussian with known variance . 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 is a gaussian martingale, and we conjecture that they are also optimal in the general case.
Mots clés : statistics of diffusions, measurement errors, LAN property
@article{PS_2001__5__243_0, author = {Gloter, Arnaud and Jacod, Jean}, title = {Diffusions with measurement errors. {II.} {Optimal} estimators}, journal = {ESAIM: Probability and Statistics}, pages = {243--260}, publisher = {EDP-Sciences}, volume = {5}, year = {2001}, mrnumber = {1875673}, zbl = {1009.60065}, language = {en}, url = {http://www.numdam.org/item/PS_2001__5__243_0/} }
Gloter, Arnaud; Jacod, Jean. Diffusions with measurement errors. II. Optimal estimators. ESAIM: Probability and Statistics, Tome 5 (2001), pp. 243-260. http://www.numdam.org/item/PS_2001__5__243_0/
[1] On estimating the diffusion coefficient. J. Appl. Probab. 24 (1987) 105-114. | MR | Zbl
,[2] On the estimation of the diffusion coefficient for multidimensional diffusion processes. Ann. Inst. H. Poincaré Probab. Statist. 29 (1993) 119-153. | Numdam | Zbl
and ,[3] Diffusion with measurement error. I. Local Asymptotic Normality (2000). | Numdam | MR | Zbl
and ,[4] Limit Theorems for Stochastic Processes. Springer-Verlag, Berlin (1987). | MR | Zbl
and ,[5] On continuous conditional Gaussian martingales and stable convergence in law, Séminaire Proba. XXXI. Springer-Verlag, Berlin, Lecture Notes in Math. 1655 (1997) 232-246. | Numdam | MR | Zbl
,[6] Fitting diffusion and trend in noise via Mercer expansion, in Proc. 7th Int. Conf. on Analytical and Stochastic Modeling Techniques. Hamburg (2000).
and ,[7] On stable sequences of events. Sankyā Ser. A 25 (1963) 293-302. | MR | Zbl
,