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Article Dans Une Revue Journal of Statistical Planning and Inference Année : 2011

Testing Inverse Problems : a direct or an indirect problem ?

Résumé

In this paper, we consider ill-posed inverse problems models $Y=Tf+\epsilon\xi$ where $T$ denotes a compact operator, $\epsilon$ a noise level, $\xi$ a Gaussian white noise and $f$ the function of interest. Recently, minimax rates of testing in such models have been obtained in various situations, both from asymptotic and non-asymptotic point of views. Nevertheless, it seems necessary to propose tests strategies attaining theses rates, being easy to implement and robust with respect to the characteristics of the operator. In particular, we prove that the inversion of the operator is not always necessary. This result provides interesting perspectives, for instance in the specific cases where the operator is unknown or difficult to handle.

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Dates et versions

hal-00528909 , version 1 (22-10-2010)

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  • HAL Id : hal-00528909 , version 1

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Béatrice Laurent, Jean-Michel Loubes, Clément Marteau. Testing Inverse Problems : a direct or an indirect problem ?. Journal of Statistical Planning and Inference, 2011, 141, pp.1849-1861. ⟨hal-00528909⟩
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