Abstract
In this paper, a new estimator for a conditional quantile is proposed by using the empirical likelihood method and local linear fitting when some auxiliary information is available. The asymptotic normality of the estimator at both boundary and interior points is established. It is shown that the asymptotic variance of the proposed estimator is smaller than those of the usual kernel estimators at interior points, and that the proposed estimator has the desired sampling properties at both boundary and interior points. Therefore, no boundary modifications are required in our estimation.
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