Yao, Q.W. and Tong, H.W. (1998) Cross-validatory bandwidth selections for regression estimation based on dependent data. Journal of Statistical Planning and Inference, 68 (2). pp. 387-415. ISSN 0378-3758.
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Abstract
We suggest a simple and fast method to determine the bandwidth in kernel regression. The method can be viewed as a generalized cross-validation. We have proved asymptotic optimality of the proposed bandwidth selector under the assumption that the observations are strictly stationary and rho-mixing. Simulation has been conducted to compare the performance of various cross-validation bandwidth selectors applied to dependent data, which shows that the ordinary cross-validation method is quite stable in regression estimation with random design even when the data are highly correlated.
| Item Type: | Article |
|---|---|
| Uncontrolled keywords: | bandwidth; cross-validation; kernel estimation; locally linear regression; rho-mixing |
| Subjects: | Q Science > QA Mathematics (inc Computing science) > QA273 Probabilities |
| Depositing User: | Tara Puri |
| Date Deposited: | 24 Mar 2009 11:12 |
| Last Modified: | 24 Mar 2009 11:12 |
| Resource URI: | http://kar.kent.ac.uk/id/eprint/17289 (The current URI for this page, for reference purposes) |
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