Large deviations of consistent parameter estimates in diffusions

Research output: Contribution to journalConference articlepeer-review

Abstract

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.

Original languageEnglish
Pages (from-to)2193-2198
Number of pages6
JournalProceedings of the IEEE Conference on Decision and Control
Volume3
StatePublished - 1 Dec 1994
Externally publishedYes
EventProceedings of the 2nd IEEE International Symposium on Requirements Engineering - York, Engl
Duration: 27 Mar 199529 Mar 1995

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