Abstract
This paper defines and studies for independent identically distributed observations a new parametric estimation procedure which is asymptotically efficient under a specified regular parametric family of densities and is minimax robust in a small Hellinger metric neighborhood of the given family. Associated with the estimator is a goodness-of-fit statistic which assesses the adequacy of the chosen parametric model. The fitting of a normal location-scale model by the new procedure is exhibited numerically on clear and on contaminated data.
Citation
Rudolf Beran. "Minimum Hellinger Distance Estimates for Parametric Models." Ann. Statist. 5 (3) 445 - 463, May, 1977. https://doi.org/10.1214/aos/1176343842
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