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ASYMPTOTIC STABILITY OF THE OSCV SMOOTHING PARAMETER SELECTION
Abstract:The smoothing parameter selection by the one-sided cross-validation (OSCV) method is completely automatic in that it does not require extra parameters estimation. Also it reduces the variability comparable to that of plug-in rules. In this paper we derive analytically the asymptotic variance of the smoothing parameter selected by OSCV. It shows the dependency of the stability on the one-sided kerenl and tells the possibility of the optimal one-sided kernel which minimizes the asymptotic variability.
Keywords:Cross-validation  One-sided cross-validation  Nonparametric regression  Optimal bandwidths
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