scholarly journals Combining local and global smoothing in multivariate density estimation

Stat ◽  
2016 ◽  
Vol 5 (1) ◽  
pp. 338-348 ◽  
Author(s):  
Adelchi Azzalini



2010 ◽  
Vol 37 (4) ◽  
pp. 413-427
Author(s):  
Karol Dziedziul ◽  
Piotr Paluszek


1994 ◽  
Vol 42 (10) ◽  
pp. 2795-2810 ◽  
Author(s):  
Jenq-Neng Hwang ◽  
Shyh-Rong Lay ◽  
A. Lippman




Author(s):  
Xiaochen Zeng

This paper discusses the uniformly strong convergence of multivariate density estimation with moderately ill-posed noise over a bounded set. We provide a convergence rate over Besov spaces by using a compactly supported wavelet. When the model degenerates to one-dimensional noise-free case, the convergence rate coincides with that of Giné and Nickl’s (Ann. Probab., 2009 or Bernoulli, 2010). Our result can also be considered as an extension of Masry’s theorem (Stoch. Process. Appl., 1997) to some extent.



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