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Asymptotic Results for an L-1-norm Kernel Estimator of the Conditional Quantile for Functional Dependent Data with Application to Climatology
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Asymptotic Results for an L-1-norm Kernel Estimator of the Conditional Quantile for Functional Dependent Data with Application to Climatology

Ali Laksaci, Mohamed Lemdani and Elias Quid Said
Sankhya. Series. A, Vol.73(1), pp.125-141
01/02/2011

Abstract

Mathematics Physical Sciences Science & Technology Statistics & Probability
In this paper, we study an L-l-norm kernel estimator of the conditional quantile (CQ) of a scalar response variable Y given a random variable (rv) X taking values in a semi -metric space. The almost complete (a. co.) consistency and the asymptotic normality of this estimate are obtained when the sample is an a -mixing sequence. We illustrate our methodology by applying the estimator to climatological data.

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