Email this article Kernel estimation of the regression mode for fixed design model
Abstract
In this paper, we study the problem of estimating nonparametrically the regression mode for fixed design model. We suppose the error random variables are independent. The joint asymptotic normality of the regression mode estimator at different fixed design points is established under some regularity conditions. The performance of the proposed estimator is tested via a simulation study.
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