Adaptive kernel-type estimator for square-integrable distribution density
Here an adaptive kernel-type estimator of distribution density is considered. For a certain class of densities it is shown that the mean integrated square error (MISE) of the considered estimator is asymptotically equal to the minimum MISE in the class of all possible kernel-type estimators with kernels independent of the sample.
scientific article; zbMATH DE number 4054810