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Annals of Statistics
Variable window width kernel density estimators, with the width varying proportionally to the square root of the density, have been thought to have superior asymptotic properties. The rate of convergence has been claimed to be as good as those typical for higher order kernels, which makes the variable width estimators more attractive because no adjustment is needed to handle the negativity usually entailed by the latter. However, in a recent paper, Scott and Terrell show that in one importantdoi:10.1214/aos/1176324451 fatcat:hhmjrqnozvetll2s3pw5t2ptvy