Working paper

Consistent Density Deconvolution under Partially Known Error Distribution

Maik Schwarz, and Sébastien Van Bellegem

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 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.

Keywords

deconvolution; error measurement; density estimation;

Reference

Maik Schwarz, and Sébastien Van Bellegem, Consistent Density Deconvolution under Partially Known Error Distribution, TSE Working Paper, n. 09-097, October 6, 2009.

See also

Published in

TSE Working Paper, n. 09-097, October 6, 2009