Référence

Maik Schwarz et Sébastien Van Bellegem, « Consistent Density Deconvolution under Partially Known Error Distribution », IDEI Working Paper, n° 632, 6 octobre 2009.

Résumé

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.

Mots-clés

deconvolution; error measurement; density estimation;