Wavelet estimations for heteroscedastic super smooth errors

Jinru Wang and Wei Liu

Communications in Statistics - Theory and Methods, 2019, vol. 48, issue 10, 2356-2371

Abstract: The observed data are usually contaminated by various errors in practical applications. This paper deals with the density deconvolution problems with super smooth errors under heteroscedastic situation. We provide a new wavelet estimator and investigate its upper bound of Lp risk (1≤p

Date: 2019
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DOI: 10.1080/03610926.2018.1465086

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