Robust regression function estimation |
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Authors: | Wolfgang Härdle |
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Institution: | University of Heidelberg, Heidelberg, Federal Republic of Germany |
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Abstract: | A robust estimator of the regression function is proposed combining kernel methods as introduced for density estimation and robust location estimation techniques. Weak and strong consistency and asymptotic normality are shown under mild conditions on the kernel sequence. The asymptotic variance is a product from a factor depending only on the kernel and a factor similar to the asymptotic variance in robust estimation of location. The estimation is minimax robust in the sense of Huber (1964). Robust estimation of a location parameter. Ann. Math. Statist.33 73–101. |
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Keywords: | 62F35 62G05 62J02 Nonparametric regression kernel estimation robust smoothing |
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