The purpose of this paper is to investigate kernel density estimators for spatial processes with linear or nonlinear structures. Sufficient conditions for such estimators to converge in L 1 are obtained under extremely general, verifiable conditions. The results hold for mixing as well as for nonmix
Kernel regression estimation for continuous spatial processes
β Scribed by S. Dabo-Niang; A. -F. Yao
- Book ID
- 111503688
- Publisher
- Allerton Press Inc
- Year
- 2007
- Tongue
- English
- Weight
- 842 KB
- Volume
- 16
- Category
- Article
- ISSN
- 1066-5307
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