Yao, Qiwei, Tong, Howell (1994) On Subset-Selection in Nonparametric Stochastic Regration. Statistica Sinica, 4 (1). pp. 51-70. ISSN 1017-0405. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:20120)
| The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided. |
Abstract
This paper is concerned with the use of a cross-validation method based on the kernel estimate of the conditional mean for the subset selection of stochastic regressors within the framework of non-linear stochastic regression. Under the assumption that the observations are strictly stationary and absolutely regular, we show that the cross-validatory selection is consistent. Furthermore, two kinds of asymptotic efficiency of the selected model are proved. Both simulated and real data are used as illustrations.
| Item Type: | Article |
|---|---|
| Uncontrolled keywords: | ABSOLUTELY REGULAR; CROSS-VALIDATION; EFFICIENCY; KERNEL ESTIMATION; HETEROSCEDASTICITY; NONLINEAR STOCHASTIC REGRESSION; SUBSET SELECTION |
| Subjects: | H Social Sciences > HA Statistics |
| Divisions: | Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Mathematics, Statistics and Actuarial Science |
| Depositing User: | P. Ogbuji |
| Date Deposited: | 09 Jun 2009 11:22 UTC |
| Last Modified: | 05 Nov 2024 09:57 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/20120 (The current URI for this page, for reference purposes) |
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