Support estimation via moment estimation in presence of noise

Author: Meister, Alexander

Source: Statistics, Volume 40, Number 3, June 2006 , pp. 259-275(17)

Publisher: Taylor and Francis Ltd

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This note deals with the problem of estimating the support of a distribution function when the empirical data are contaminated. An easily computable estimation method based on moment estimation is introduced. Unlike earlier approaches, these estimators also cover situations in which the sharpness of the target distribution at the support boundaries is arbitrarily low and in which the distribution is discontinuous at several points within the support. General consistency results for the estimators are achieved and rates of convergence are studied in the case of normal measurement error. The practical performance of the estimation procedure is studied in a simulation section.

Keywords: Deconvolution; Errors-in-variables; Moment estimation; Support estimation

Document Type: Research Article


Affiliations: Institut für Stochastik und Anwendungen, Universität Stuttgart, D-70569, Stuttgart, Germany

Publication date: June 1, 2006

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