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Journal Articles Metrika Year : 2021

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

Ali Laksaci
  • Function : Author
Mustapha Rachdi
  • Function : Author

Abstract

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 and versions

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

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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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