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Activity Number: 121
Type: Invited
Date/Time: Monday, July 30, 2007 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract - #307815
Title: On Optimal Smoothing Parameter Choice in Deconvolution Problems
Author(s): Peter Hall and Aurore Delaigle*+
Companies: The University of Melbourne and University of Bristol
Address: Department of Mathematics, Bristol, BS8 1TW, United Kingdom
Keywords: deconvolution ; density estimation ; smoothing parameter ; regression
Abstract:

The SIMEX method for deconvolution enjoys a range of attractive features, among them the fact it needs little by way of tuning. However, it also suffers drawbacks, including inconsistency. For reasons such as this, and although SIMEX has enthusiasts and adherents, it is not as widely used as it might be. We suggest that SIMEX be employed for smoothing-parameter choice in other deconvolution methods (based on, for example, kernels, orthogonal series or ridging), rather than for constructing estimators itself. In this context SIMEX has very broad application, not just to different estimator types but to different deconvolution problems.

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Revised September, 2007