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

Barry, J. and Diggle, Peter J. (1995) Choosing the smoothing parameter in a Fourier approach to non-parametric deconvolution of a density estimate. Journal of Nonparametric Statistics, 4 (3). pp. 223-232. ISSN 1048-5252

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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.

Item Type:
Journal Article
Journal or Publication Title:
Journal of Nonparametric Statistics
Uncontrolled Keywords:
/dk/atira/pure/researchoutput/libraryofcongress/qa
Subjects:
ID Code:
19553
Deposited By:
Deposited On:
11 Nov 2008 11:21
Refereed?:
Yes
Published?:
Published
Last Modified:
01 Jan 2020 06:15