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Large Deviation Laws in Recursive Estimation

Authors: [tex2html_wrap4420]D. Levanony

Investigator username: levanony

Category: systems and control theory


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. Such measures of convergence rates are considerably stronger than the widely used central limit theorems. First, conditional LD limits are obtained in an indirect way, by utilizing a general martingale law. Those are then applied to derive simple stopping rules which have direct practical significance.