Nonparametric recursive estimation of the derivative of the regression function with application to sea shores water quality
DURRIEU, Gilles
Université de la Nouvelle-Calédonie [UNC]
Laboratoire de Mathématiques de Bretagne Atlantique [LMBA]
Université de la Nouvelle-Calédonie [UNC]
Laboratoire de Mathématiques de Bretagne Atlantique [LMBA]
DURRIEU, Gilles
Université de la Nouvelle-Calédonie [UNC]
Laboratoire de Mathématiques de Bretagne Atlantique [LMBA]
< Reduce
Université de la Nouvelle-Calédonie [UNC]
Laboratoire de Mathématiques de Bretagne Atlantique [LMBA]
Language
en
Article de revue
This item was published in
Statistical Inference for Stochastic Processes. 2019, vol. 22, n° 1, p. 17-40
Springer Verlag
English Abstract
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 ...Read more >
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.Read less <
ANR Project
Centre de Mathématiques Henri Lebesgue : fondements, interactions, applications et Formation - ANR-11-LABX-0020
Origin
Hal imported