On subset selection in non-parametric stochastic regression

Qiwei Yao and Howell Tong

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

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.

Keywords: Absolutely regular; cross-validation; efficiency; kernel estimation; heteroscedasticity; non-linear stochastic regression; subset selection (search for similar items in EconPapers)
JEL-codes: C1 (search for similar items in EconPapers)
Date: 1994-01
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Citations: View citations in EconPapers (16)

Published in Statistica Sinica, January, 1994, 4(1), pp. 51-70. ISSN: 1017-0405

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