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Article Dans Une Revue Statistical Inference for Stochastic Processes Année : 2019

Nonparametric recursive estimation of the derivative of the regression function with application to sea shores water quality

Résumé

This paper is devoted to the nonparametric estimation of the derivative of the regression function in a nonparametric regression model. We implement a very efficient and easy to handle statistical procedure based on the derivative of the recursive Nadaraya–Watson estimator. We establish the almost sure convergence as well as the asymptotic normality for our estimates. We also illustrate our nonparametric estimation procedure on simulated data and real life data associated with sea shores water quality and valvometry.
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Dates et versions

hal-02470351 , version 1 (07-02-2020)

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  • HAL Id : hal-02470351 , version 1

Citer

Gilles Durrieu, Sami Capderou, Bernard Bercu. Nonparametric recursive estimation of the derivative of the regression function with application to sea shores water quality. Statistical Inference for Stochastic Processes, 2019, 22 (1), pp.17-40. ⟨hal-02470351⟩
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