An efficient cross-validation algorithm for window width selection for nonparametric kernel regression |
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Authors: | Jeff Racine |
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Affiliation: | Department of Economics , University of California , 9500 Gilman Drive, San Diego, La Jolla, 92093, CA |
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Abstract: | This paper presents an approach to cross-validated window width choice which greatly reduces computation time, which can be used regardless of the nature of the kernel function, and which avoids the use of the Fast Fourier Transform. This approach is developed for window width selection in the context of kernel estimation of an unknown conditional mean. |
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Keywords: | kernel regression window width selection cross-validation computational efficiency |
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