估計二維函數曲面(2/2)
Date Issued
2002-10-31
Date
2002-10-31
Author(s)
DOI
902118M002011
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 minimizing deviations of of elementary surface estimates along a linear or quadratic
curve. Once a contour estimate has been obtained, the final surface estimate is computed by
averaging conventaional surface estimates along a portion of the contour. Theoretical and
numerical properties of the technique are discussed.
Subjects
Bandwidth
boundary effect
kernel method
nonparametric density estimation
nonparametric regression
variance reduction
Publisher
臺北市：國立臺灣大學數學系暨研究所
Type
report
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