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.
Original language | English |
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Pages (from-to) | 375-397 |
Number of pages | 23 |
Journal | Journal of Multivariate Analysis |
Volume | 86 |
Issue number | 2 |
DOIs | |
Publication status | Published - Aug 2003 |
User-Defined Keywords
- Bandwidth
- Boundary effect
- Kernel method
- Nonparametric density estimation
- Nonparametric regression
- Variance reduction