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 |
|---|---|
| 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