An Alternative View of the Deconvolution Problem

@inproceedings{Delaigle2007AnAV,
  title={An Alternative View of the Deconvolution Problem},
  author={Aurore Delaigle},
  year={2007}
}
The deconvolution kernel density estimator is a popular technique for solving the deconvolution problem, where the goal is to estimate a density from a sample of contaminated observations. Although this estimator is optimal, it suffers from two major drawbacks: it converges at very slow rates (inherent to the deconvolution problem) and can only be calculated when the density of the errors is completely known. These properties, however, follow from a classical asymptotic view of the problem… CONTINUE READING
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