Abstract
We compute a variance lower bound for unbiased estimators in specified statistical models. The construction of the bound is related to the original Cramér-Rao bound, although it does not require the differentiability of the model. Moreover, we show our efficiency bound to be always greater than the Cramér-Rao bound in smooth models, thus providing a sharper result.
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