Estimating the Error Distribution Function in Nonparametric Regression with Multivariate Covariates
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چکیده
We consider nonparametric regression models with multivariate covariates and estimate the regression curve by an undersmoothed local polynomial smoother. The resulting residual-based empirical distribution function is shown to differ from the errorbased empirical distribution function by the density times the average of the errors, up to a uniformly negligible remainder term. This result implies a functional central limit theorem for the residual-based empirical distribution function.
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تاریخ انتشار 2008