# Generalized estimators, slope, efficiency, and fisher information bounds

@article{Vos2022GeneralizedES, title={Generalized estimators, slope, efficiency, and fisher information bounds}, author={Paul Vos}, journal={Information Geometry}, year={2022} }

Point estimators may not exist, need not be unique, and their distributions are not parameter invariant. Generalized estimators provide distributions that are parameter invariant, unique, and exist when point estimates do not. Comparing point estimators using variance is less use-ful when estimators are biased. A squared slope Λ is deﬁned that can be used to compare both point and generalized estimators and is unaﬀected by bias. Fisher information I and variance are fundamentally diﬀerent…

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