Yao, Qiwei and Tong, Howell (1994) On subset selection in non-parametric stochastic regression. Statistica Sinica, 4 (1). pp. 51-70. ISSN 1017-0405
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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 |
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| Official URL: | http://www3.stat.sinica.edu.tw/statistica/ |
| Additional Information: | © 1994 Academia Sinica |
| Uncontrolled Keywords: | Absolutely regular, cross-validation, efficiency, kernel estimation, heteroscedasticity, non-linear stochastic regression, subset selection |
| Library of Congress subject classification: | H Social Sciences > H Social Sciences (General) H Social Sciences > HA Statistics |
| Sets: | Collections > Economists Online Departments > Economics Departments > Statistics |
| Rights: | http://www.lse.ac.uk/library/rights/LSERO.htm |
| URL: | http://eprints.lse.ac.uk/6409/ |
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