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Article Dans Une Revue Metrika Année : 2021

Uniform consistency in number of neighbors of the kNN estimator of the conditional quantile model

Ali Laksaci
  • Fonction : Auteur
Mustapha Rachdi
  • Fonction : Auteur

Résumé

We are interested in the efficiency of the nonparametric estimation of the conditional quantile when the response variable is a scalar given a functional covariate. To do this, we adopt a technique which is based on the use of the k-Nearest Neighbors procedure to build a kernel estimator of this model. Then, we establish the uniform conver- gence in number of neighbors of the constructed estimator. Moreover, we discuss the optimal choices of different parameters that are involved in the model as well as the impacts of the obtained results. Finally, we show the applicability and efficiency of our methodology to investigate the fuel quality by using a Near-infrared spectroscopy dataset.
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Dates et versions

hal-04412549 , version 1 (23-01-2024)

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Citer

Ali Laksaci, Elias Ould Saïd, Mustapha Rachdi. Uniform consistency in number of neighbors of the kNN estimator of the conditional quantile model. Metrika, 2021, 84 (6), pp.895-911. ⟨10.1007/s00184-021-00806-5⟩. ⟨hal-04412549⟩
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