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Cross-validation and non-parametric k nearest-neighbour estimation

Desheng Ouyang, Dong Li () and Qi Li

Econometrics Journal, 2006, vol. 9, issue 3, 448-471

Abstract: In this paper we consider the problem of estimating a non-parametric regression function using the k nearest-neighbour method. We provide asymptotic theories for the least-squares cross validation (CV) selected smoothing parameter k for both local constant and local linear estimation methods. We also establish the asymptotic normality results for the resulting non-parametric regression function estimators. Some limited Monte Carlo experiments show that the CV method performs well in finite sample applications. Copyright Royal Economic Society 2006

Date: 2006
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Econometrics Journal is currently edited by Richard J. Smith, Oliver Linton, Pierre Perron, Jaap Abbring and Marius Ooms

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Handle: RePEc:ect:emjrnl:v:9:y:2006:i:3:p:448-471