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On subset selection in non-parametric stochastic regression

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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.

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en

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application/pdf

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http://eprints.lse.ac.uk/6409/1/On_subset_selection_in_non-parametric_stochastic_regression%28LSERO%29.pdf

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