Yao, Q.W and Tong, H.W (1994) On Subset-Selection in Nonparametric Stochastic Regration. Statistica Sinica, 4 (1). pp. 51-70. ISSN 1017-0405.
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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.
|Uncontrolled keywords:||ABSOLUTELY REGULAR; CROSS-VALIDATION; EFFICIENCY; KERNEL ESTIMATION; HETEROSCEDASTICITY; NONLINEAR STOCHASTIC REGRESSION; SUBSET SELECTION|
|Subjects:||H Social Sciences > HA Statistics|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics|
|Depositing User:||P. Ogbuji|
|Date Deposited:||09 Jun 2009 11:22|
|Last Modified:||09 Jun 2009 11:22|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/20120 (The current URI for this page, for reference purposes)|
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