Non-asymptotic Bandwidth Selection for Density Estimation of Discrete Data
β Scribed by Zdravko I. Botev; Dirk P. Kroese
- Book ID
- 106457292
- Publisher
- Springer US
- Year
- 2008
- Tongue
- English
- Weight
- 461 KB
- Volume
- 10
- Category
- Article
- ISSN
- 1387-5841
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
With mild restrictions placed on the kernel, kernel estimates of an unknown multivariatc density are investigated when the observed data are dependent. A modified cross validation rule, the simple 'leave-(2P + 1)-o&' version of simple cross validation, is considered for bandwidth selection. Under th
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