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Article Dans Une Revue Metrika Année : 2020

Regression function estimation on non compact support in an heteroskedastik model

Fabienne Comte
Valentine Genon-Catalot
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Résumé

We study the problem of non parametric regression function estimation on non necessarily compact support in a heteroskedastic model with unbounded variance. A collection of least squares projection estimators on m-dimensional functional linear spaces is built. We prove new risk bounds for the estimator with fixed m and propose a new selection procedure relying on inverse problems methods leading to an adaptive estimator. Contrary to more standard cases, the data-driven dimension is chosen within a random set and the penalty is random. Examples and numerical simulations results show that the procedure is easy to implement and provides satisfactory estimators.
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Dates et versions

hal-02009555 , version 1 (06-02-2019)

Identifiants

  • HAL Id : hal-02009555 , version 1

Citer

Fabienne Comte, Valentine Genon-Catalot. Regression function estimation on non compact support in an heteroskedastik model. Metrika, 2020, 83, pp.93-128. ⟨hal-02009555⟩
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