Hellinger distance and Kullback--Leibler loss for the kernel density estimator

Yuichiro Kanazawa

Statistics & Probability Letters, 1993, vol. 18, issue 4, 315-321

Abstract: The optimal window width, which asymptotically minimizes mean Hellinger distance between the kernel estimator and density, is known to be equivalent to the one that maximizes expected Kullback--Leibler loss for compactly supported densities. Implications of the result are discussed.

Keywords: ams; 1980; Subject; Classification; Primary; 62G05; Secondary; 62E20; Akaike's; information; criterion; Hellinger; distance; histogram; kernel; density; estimator; Kullback--Leibler; loss; likelihood; cross-validation (search for similar items in EconPapers)
Date: 1993
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Citations: View citations in EconPapers (2)

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