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Choosing the smoothing parameter in a Fourier approach to non-parametric deconvolution of a density estimate.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>1995
<mark>Journal</mark>Journal of Nonparametric Statistics
Issue number3
Volume4
Number of pages10
Pages (from-to)223-232
Publication StatusPublished
<mark>Original language</mark>English

Abstract

In this note we derive a weighted non-linear least squares procedure for choosing the smoothing parameter in a Fourier approach to deconvolution of a density estimate. The method has the advantage over a previous procedure in that it is robust to the range of frequencies over which the model is fitted. A simulation study with different parametric forms for the densities in the convolution equation demonstrates that the method can perform well in practice. A truncated form of the estimator generally has a lower mean asymptotic integrated squared error than an alternative, continuously damped form, but the damped method gives better estimates of tail probabilities.