This paper studies the risks and bandwidth choices of a kernel estimate of the underlying density when the data are obtained from s independent biased samples. The main results of this paper give the asymptotic representation of the integrated squared errors and the mean integrated squared errors of
Data-driven choice of the smoothing parametrization for kernel density estimators
✍ Scribed by José E. Chacón
- Publisher
- John Wiley and Sons
- Year
- 2009
- Tongue
- French
- Weight
- 457 KB
- Volume
- 37
- Category
- Article
- ISSN
- 0319-5724
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