Generalized estimators (sample-to-function maps) admit a uniform information bound attained by the score, explaining classical estimation strains without overturning its theorems.
The Geometry of Estimating Functions in the Presence of Nuisance Parameters 1 , volume =
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A New Look at the Classical Estimation Problem
Generalized estimators (sample-to-function maps) admit a uniform information bound attained by the score, explaining classical estimation strains without overturning its theorems.