A lower bound on the mean-square error in random parameter estimation (Corresp.)

Authors:
A. Weiss;E. Weinstein
Affiliations:
-;-
Venue:
IEEE Transactions on Information Theory
Year:
2006

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Abstract

A new lower bound on mean-square error in parameter estimation is presented. The bound is tighter than the Cramér-Rao and Bobrovsky-Zakai lower bounds. It requires no bias or regularity assumptions, it is computationally simple, and it can be applied to estimates of vector parameters or functions of the parameters.