Communications for Statistical Applications and Methods

The Korean Statistical Society (한국통계학회)
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A Support Vector Method for the Deconvolution Problem

  • Received : 20100200
  • Accepted : 20100300
  • Published : 2010.05.31
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Abstract

This paper considers the problem of nonparametric deconvolution density estimation when sample observa-tions are contaminated by double exponentially distributed errors. Three different deconvolution density estima-tors are introduced: a weighted kernel density estimator, a kernel density estimator based on the support vector regression method in a RKHS, and a classical kernel density estimator. The performance of these deconvolution density estimators is compared by means of a simulation study.

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References

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