On the mean L1-error in the heteroscedastic deconvolution problem with compactly supported noises

Cao Xuan Phuong, Dang Duc Trong and Tran Quoc Viet

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 16, 3871-3892

Abstract: We study the heteroscedastic deconvolution problem when random noises have compactly supported densities. In this context, the Fourier transforms of the densities can vanish on the real line. We propose a truncated type of estimator for target density and derive the convergence rate of the mean L1-error uniformly over a class of target densities. A lower bound for the mean L1-error is also established. Some simulations will be given to illustrate the performance of the proposed estimator.

Date: 2018
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DOI: 10.1080/03610926.2017.1364389

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