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Faculty of Economics

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Linton, O. and Jacho-Chavez, D.

On internally corrected and symmetrized kernel estimators for nonparametric regression

TEST

Abstract: We investigate the properties of a kernel-type multivariate regression estimator first proposed by Mack and Müller (Sankhya 51:59–72, 1989) in the context of univariate derivative estimation. Our proposed procedure, unlike theirs, assumes that bandwidths of the same order are used throughout; this gives more realistic asymptotics for the estimation of the function itself but makes the asymptotic distribution more complicated. We also propose a modification of this estimator that has a symmetric smoother matrix, which makes it admissible, unlike some other common regression estimators. We compare the performance of the estimators in a Monte Carlo experiment.

Author links: Oliver Linton  

Publisher's Link: http://link.springer.com/article/10.1007%2Fs11749-009-0145-y



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