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Article Dans Une Revue Journal of Computational and Applied Mathematics Année : 2020

Nonparametric estimation in a regression model with additive and multiplicative noise

Résumé

In this paper, we consider an unknown functional estimation problem in a general nonparametric regression model with the feature of having both multiplicative and additive noise.We propose two new wavelet estimators in this general context. We prove that they achieve fast convergence rates under the mean integrated square error over Besov spaces. The obtained rates have the particularity of being established under weak conditions on the model. A numerical study in a context comparable to stochastic frontier estimation (with the difference that the boundary is not necessarily a production function) supports the theory.
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Dates et versions

hal-02159579 , version 1 (18-06-2019)
hal-02159579 , version 2 (20-06-2020)

Identifiants

Citer

Christophe Chesneau, Salima El Kolei, Junke Kou, Fabien Navarro. Nonparametric estimation in a regression model with additive and multiplicative noise. Journal of Computational and Applied Mathematics, 2020, 380, pp.112971. ⟨10.1016/j.cam.2020.112971⟩. ⟨hal-02159579v2⟩
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