Consistent density deconvolution under partially known error distribution

Schwarz, Maik;Van Bellegem, Sébastien
(2010) Statistics & Probability Letters — Vol. 80, n° 3-4, p. 236-241 (2010)

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Abstract
We estimate the distribution of a real-valued random variable from contaminated observations. The additive error is supposed to be normally distributed, but with an unknown variance. The distribution is identifiable from the observations if we restrict the class of considered distributions by a simple condition in the time domain. A minimum distance estimator is shown to be consistent imposing only a slightly stronger assumption than the identification condition. (C) 2009 Elsevier B.V. All rights reserved.
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  • Institution iconUCLouvainSSH/IMAQ - Institut multidisciplinaire pour la modélisation et l'analyse quantitative

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Schwarz, M., & Van Bellegem, S. (2010). Consistent density deconvolution under partially known error distribution. Statistics & Probability Letters, 80(3-4), 236-241. https://doi.org/10.1016/j.spl.2009.10.012 (Original work published 2010)