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Regression estimation by local polynomial fitting for multivariate data streams

Abstract : In this paper we study a local polynomial estimator of the regression function and its derivatives. We propose a sequential technique based on a multivariate counterpart of the stochastic approximation method for successive experiments for the local polynomial estimation problem. We present our results in a more general context by considering the weakly dependent sequence of stream data, for which we provide an asymptotic bias-variance decomposition of the considered estimator. Additionally, we study the asymptotic normality of the estimator and we provide algorithms for the practical use of the method in data streams framework.
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https://hal.archives-ouvertes.fr/hal-01592783
Contributor : Romain Boisselet <>
Submitted on : Monday, September 25, 2017 - 1:52:07 PM
Last modification on : Friday, March 13, 2020 - 2:43:35 PM

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Aboubacar Amiri, Baba Thiam. Regression estimation by local polynomial fitting for multivariate data streams. Statistical Papers, Springer Verlag, 2016, 59, pp.813-843. ⟨10.1007/s00362-016-0791-6⟩. ⟨hal-01592783⟩

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