High order data sharpening for density estimation

It is shown that data sharpening can be used to produce density estimators that enjoy arbitrarily high orders of bias reduction. Practical advantages of this approach, relative to competing methods, are demonstrated. They include the sheer simplicity of the estimators, which makes code for computing them particularly easy to write, very good mean‐squared error performance, reduced `wiggliness' of estimates and greater robustness against undersmoothing.

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