Consistent density deconvolution under partially known error distribution

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.

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Year of publication:	2010
Authors:	Schwarz, Maik ; Van Bellegem, Sébastien
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 80.2010, 3-4, p. 236-241
Publisher:	Elsevier

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10008551112