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Empirical Likelihood for Nonparametric Models Under Linear Process Errors

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Summary

In this paper, we study the construction of confidence intervals for a nonparametric regression function under linear process errors by using the blockwise technique. It is shown that the blockwise empirical likelihood (EL) ratio statistic is asymptotically inline image distributed. The result is used to obtain EL based confidence intervals for the nonparametric regression function. The finite-sample performance of the method is evaluated through a simulation study.

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