Journal of Computational and Applied Mathematics2022,Vol.40017.DOI:10.1016/j.cam.2021.113752

Uniform convergence rates for wavelet curve estimation in sup-norm loss

Zhou, Xingcai
Journal of Computational and Applied Mathematics2022,Vol.40017.DOI:10.1016/j.cam.2021.113752

Uniform convergence rates for wavelet curve estimation in sup-norm loss

Zhou, Xingcai1
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作者信息

  • 1. Nanjing Audit Univ
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Abstract

This paper presents the rates of uniform strong consistency of wavelet estimation for nonparametric function in sup-norm loss by introducing an empirical process approach. A compact support assumption on the explanatory variable is commonly used in nonparametric regression analysis. In the article, we consider the wavelet estimation analysis without any assumption on the compacity of the support of the explanatory variable. The optimal uniform convergence rates of the wavelet estimators are achieved by suitably choosing resolution level. These results are useful for wavelet theory on nonparametric signal recovery and analysis. (C) 2021 Elsevier B.V. All rights reserved.

Key words

Wavelet estimator/Uniform consistency/Sup-norm loss/DENSITY-ESTIMATION/CONSISTENCY/REGRESSION/INEQUALITIES/LOGARITHM/SUMS/LAW

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出版年

2022
Journal of Computational and Applied Mathematics

Journal of Computational and Applied Mathematics

EISCI
ISSN:0377-0427
参考文献量39
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