Reducing variance in nonparametric surface estimation |
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Authors: | Ming-Yen Cheng Peter Hall |
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Affiliation: | a Centre for Mathematics and its Applications, Australian National University, Canberra, ACT 0200, Australia;b Department of Mathematics, National Taiwan University, Taipei 106, Taiwan |
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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. |
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Keywords: | Bandwidth Boundary effect Kernel method Nonparametric density estimation Nonparametric regression Variance reduction |
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