Flexible Multivariate Density Estimation with Marginal Adaptation

2008 ◽  
Author(s):  
Paolo Giordani ◽  
Robert Kohn ◽  
Xiuyan Mun
Keyword(s):  
Density Estimation ◽  
Marginal Adaptation ◽  
Multivariate Density Estimation ◽  
Multivariate Density

scholarly journals Flexible Multivariate Density Estimation With Marginal Adaptation

2013 ◽  
Vol 22 (4) ◽  
pp. 814-829 ◽  
Author(s):  
Paolo Giordani ◽  
Xiuyan Mun ◽  
Minh-Ngoc Tran ◽  
Robert Kohn
Keyword(s):  
Density Estimation ◽  
Marginal Adaptation ◽  
Multivariate Density Estimation ◽  
Multivariate Density

A note on wavelet deconvolution density estimation

2017 ◽  
Vol 15 (06) ◽  
pp. 1750055 ◽  
Author(s):  
Xiaochen Zeng
Keyword(s):  
Convergence Rate ◽  
Strong Convergence ◽  
Density Estimation ◽  
Besov Spaces ◽  
One Dimensional ◽  
Bounded Set ◽  
Multivariate Density Estimation ◽  
Free Case ◽  
Ill Posed ◽  
Multivariate Density

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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