Reducing variance in nonparametric surface estimation

Ming-Yen Cheng and Peter Hall

Journal of Multivariate Analysis, 2003, vol. 86, issue 2, 375-397

Abstract: We suggest a method for reducing variance in nonparametric surface estimation. The technique is applicable to a wide range of inferential problems, including both density estimation and regression, and to a wide variety of estimator types. It is based on estimating the contours of a surface by minimising deviations of elementary surface estimates along a quadratic curve. Once a contour estimate has been obtained, the final surface estimate is computed by averaging conventional surface estimates along a portion of the contour. Theoretical and numerical properties of the technique are discussed.

Keywords: Bandwidth; Boundary; effect; Kernel; method; Nonparametric; density; estimation; Nonparametric; regression; Variance; reduction (search for similar items in EconPapers)
Date: 2003
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