Deconvolution in nonparametric statistics
نویسندگان
چکیده
In this tutorial paper we give an overview of deconvolution problems in nonparametric statistics. First, we consider the problem of density estimation given a contaminated sample. We illustrate that the classical Rosenblatt-Parzen kernel density estimator is unable to capture the full shape of the density while the presented method experiences almost no problems. Second, we use the previous estimator in a nonparametric regression framework with errors-in-variables.
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تاریخ انتشار 2012