Publication:
Density Deconvolution in a Non-standard Case of Heteroscedastic Noises

datacite.subject.fos oecd::Engineering and technology
dc.contributor.author Cao Xuan Phuong
dc.contributor.author Le Thi Hong Thuy
dc.date.accessioned 2022-11-09T11:19:17Z
dc.date.available 2022-11-09T11:19:17Z
dc.date.issued 2020
dc.description.abstract We study the density deconvolution problem with heteroscedastic noises whose densities are known exactly and Fourier-oscillating. Based on available data, we propose a nonparametric estimator depending on two regularization parameters. This estimator is shown to be consistency with respect to the mean integrated squared error. We then establish upper and lower bounds of the error over the Sobolev class of target density to give the minimax optimality of the estimator. In particular, this estimator is adaptive to the smoothness of the unknown target density. We finally demonstrate that the estimator achieves the minimax rates when the noise densities are supersmooth and ordinary smooth.
dc.identifier.doi 10.1007/s42519-020-00130-7
dc.identifier.uri http://repository.vlu.edu.vn:443/handle/123456789/1141
dc.language.iso en_US
dc.relation.ispartof Journal of Statistical Theory and Practice
dc.relation.issn 1559-8608
dc.relation.issn 1559-8616
dc.subject "Density deconvolution
dc.subject Heteroscedastic noises
dc.subject Fourier-oscillating density · Minimax rate"
dc.title Density Deconvolution in a Non-standard Case of Heteroscedastic Noises
dc.type journal-article
dspace.entity.type Publication
oaire.citation.issue 4
oaire.citation.volume 14
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