Deconvolution with unknown error distribution
نویسندگان
چکیده
منابع مشابه
Deconvolution with unknown error distribution
We consider the problem of estimating a density fX using a sample Y1, . . . , Yn from fY = fX ? fε, where fε is an unknown density function. We assume that an additional sample ε1, . . . , εm from fε is given. Estimators of fX and its derivatives are constructed using nonparametric estimators of fY and fε and applying a spectral cut-off in the Fourier domain. In this paper the rate of convergen...
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This note presents rates of convergence for the pointwise mean squared error in the deconvolution problem with estimated characteristic function of the errors. Résumé Déconvolution ponctuelle avec distribution de l’erreur inconnue. Cette note présente les vitesses de convergence pour le risque quadratique ponctuel dans le problème de déconvolution avec fonction caractéristique des erreurs estimée.
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We devise a new method of estimating a distribution in a deconvolution model with panel data and an unknown distribution of the additive errors. We prove strong consistency under a minimal condition concerning the zero sets of the involved characteristic functions.
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This paper develops a method to construct confidence bands in deconvolution when the error distribution is unknown. We work with the case where an auxiliary sample from the error distribution is available and the error density is ordinary smooth. The construction is based upon the “intermediate” Gaussian approximation and the Gaussian multiplier bootstrap, but not on explicit limit distribution...
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We consider the problem of estimating a density fX using a sample Y1,. .. , Yn from fY = fX ⋆ fǫ, where fǫ is an unknown density. We assume that an additional sample ǫ1,. .. , ǫm from fǫ is observed. Estimators of fX and its derivatives are constructed by using non-parametric estimators of fY and fǫ and by applying a spectral cutoff in the Fourier domain. We derive the rate of convergence of th...
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ژورنال
عنوان ژورنال: The Annals of Statistics
سال: 2009
ISSN: 0090-5364
DOI: 10.1214/08-aos652