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Author:

Wu, C. (Wu, C..) | Zeng, X.C. (Zeng, X.C..) | Wang, J.R. (Wang, J.R..)

Indexed by:

Scopus PKU CSCD

Abstract:

This paper considers pointwise deconvolution estimation of density functions under the local Hölder condition by wavelet method. We firstly give a lower bound of any estimator with super-smooth noises. Then the practical linear wavelet estimator is constructed to obtain the optimal convergence rate, which means that the rate coincides with the lower bound. The strong convergence rate of the defined wavelet estimator is also provided. It should be pointed out that all above estimations are adaptive. © 2019, Chinese Academy of Sciences. All right reserved.

Keyword:

Adaptivity; Optimality; Pointwise density estimation; Wavelets

Author Community:

  • [ 1 ] [Wu, C.]College of Applied Sciences, Beijing University of Technology, Beijing, 100124, China
  • [ 2 ] [Zeng, X.C.]College of Applied Sciences, Beijing University of Technology, Beijing, 100124, China
  • [ 3 ] [Wang, J.R.]College of Applied Sciences, Beijing University of Technology, Beijing, 100124, China

Reprint Author's Address:

  • [Zeng, X.C.]College of Applied Sciences, Beijing University of TechnologyChina

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Source :

Acta Mathematica Sinica, Chinese Series

ISSN: 0583-1431

Year: 2019

Issue: 5

Volume: 62

Page: 687-702

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count:

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 6

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