Bernoulli

  • Bernoulli
  • Volume 14, Number 2 (2008), 562-579.

Density estimation with heteroscedastic error

Aurore Delaigle and Alexander Meister

Full-text: Open access

Abstract

It is common, in deconvolution problems, to assume that the measurement errors are identically distributed. In many real-life applications, however, this condition is not satisfied and the deconvolution estimators developed for homoscedastic errors become inconsistent. In this paper, we introduce a kernel estimator of a density in the case of heteroscedastic contamination. We establish consistency of the estimator and show that it achieves optimal rates of convergence under quite general conditions. We study the limits of application of the procedure in some extreme situations, where we show that, in some cases, our estimator is consistent, even when the scaling parameter of the error is unbounded. We suggest a modified estimator for the problem where the distribution of the errors is unknown, but replicated observations are available. Finally, an adaptive procedure for selecting the smoothing parameter is proposed and its finite-sample properties are investigated on simulated examples.

Article information

Source
Bernoulli Volume 14, Number 2 (2008), 562-579.

Dates
First available in Project Euclid: 22 April 2008

Permanent link to this document
https://projecteuclid.org/euclid.bj/1208872118

Digital Object Identifier
doi:10.3150/08-BEJ121

Mathematical Reviews number (MathSciNet)
MR2544102

Zentralblatt MATH identifier
1155.62023

Keywords
bandwidth density deconvolution errors-in-variables heteroscedastic contamination inverse problems plug-in

Citation

Delaigle, Aurore; Meister, Alexander. Density estimation with heteroscedastic error. Bernoulli 14 (2008), no. 2, 562--579. doi:10.3150/08-BEJ121. https://projecteuclid.org/euclid.bj/1208872118.


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