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.
Original language | English (US) |
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Pages (from-to) | 223-232 |
Number of pages | 10 |
Journal | Journal of Nonparametric Statistics |
Volume | 4 |
Issue number | 3 |
DOIs | |
State | Published - Jan 1 1995 |
Externally published | Yes |
Keywords
- Deconvolution
- density estimation
- Fourier transform
- smoothing
ASJC Scopus subject areas
- Statistics, Probability and Uncertainty
- Statistics and Probability