Rates of convergence of strongly consistent parameter estimates in diffusion processes are studied via large deviations (LD) laws for the suprema of the estimation error's tail processes. First, conditional LD limits are obtained by utilizing a general martingale law. Those are then applied to derive simple stopping rules. Finally, unconditional LD lower bounds are derived by an extension of a well known direct method.
|Number of pages||6|
|Journal||Proceedings of the IEEE Conference on Decision and Control|
|State||Published - 1 Dec 1994|
|Event||Proceedings of the 2nd IEEE International Symposium on Requirements Engineering - York, Engl|
Duration: 27 Mar 1995 → 29 Mar 1995