scholarly journals Lower bounds in the convolution structure density model

Bernoulli ◽  
2017 ◽  
Vol 23 (2) ◽  
pp. 884-926 ◽  
Author(s):  
O.V. Lepski ◽  
T. Willer
Mathematics ◽  
2020 ◽  
Vol 8 (9) ◽  
pp. 1391
Author(s):  
Kaikai Cao ◽  
Xiaochen Zeng

Using kernel methods, Lepski and Willer study a convolution structure density model and establish adaptive and optimal Lp risk estimations over an anisotropic Nikol’skii space (Lepski, O.; Willer, T. Oracle inequalities and adaptive estimation in the convolution structure density model. Ann. Stat.2019, 47, 233–287). Motivated by their work, we consider the same problem over Besov balls by wavelets in this paper and first provide a linear wavelet estimate. Subsequently, a non-linear wavelet estimator is introduced for adaptivity, which attains nearly-optimal convergence rates in some cases.


Author(s):  
Parinya CHALERMSOOK ◽  
Hiroshi IMAI ◽  
Vorapong SUPPAKITPAISARN

2020 ◽  
Vol 148 (2) ◽  
pp. 321-327
Author(s):  
Rodolfo Gutiérrez-Romo ◽  
Carlos Matheus
Keyword(s):  

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