Let (X, Y ) be an R d \_R-valued regression pair, where X has a density and Y is bounded. If n i.i.d. samples are drawn from this distribution, the Nadaraya Watson kernel regression estimate in R d with Hilbert kernel K(x)=1Γ&x& d is shown to converge weakly for all such regression pairs. We also sh
β¦ LIBER β¦
The kernel estimate is relatively stable
β Scribed by Luc Devroye
- Publisher
- Springer
- Year
- 1988
- Tongue
- English
- Weight
- 691 KB
- Volume
- 77
- Category
- Article
- ISSN
- 1432-2064
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