DURRIEU, Gilles; CAPDEROU, Sami; BERCU, Bernard

Metadatos

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Licencia de uso del documento

DURRIEU, Gilles
Université de la Nouvelle-Calédonie [UNC]
Laboratoire de Mathématiques de Bretagne Atlantique [LMBA]

CAPDEROU, Sami
Institut de Mathématiques de Bordeaux [IMB]

BERCU, Bernard
Institut de Mathématiques de Bordeaux [IMB]

Idioma

Article de revue

Este ítem está publicado en

Statistical Inference for Stochastic Processes. 2019, vol. 22, n° 1, p. 17-40

Springer Verlag

Resumen en inglés

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.< Leer menos

URI

https://oskar-bordeaux.fr/handle/20.500.12278/192565

Proyecto ANR

Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation - ANR-11-LABX-0020

Orígen

Importado de Hal

Centros de investigación

Institut de Mathématiques de Bordeaux (IMB) - UMR 5251