Strong Uniform Convergence Rates of Wavelet Density Estimators with Size-Biased Data
Joint Authors
Source
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-03-06
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
This paper considers the strong uniform convergence of multivariate density estimators in Besov space Bp,qs(Rd) based on size-biased data.
We provide convergence rates of wavelet estimators when the parametric μ is known or unknown, respectively.
It turns out that the convergence rates coincide with that of Giné and Nickl’s (Uniform Limit Theorems for Wavelet Density Estimators, Ann.
Probab., 37(4), 1605-1646, 2009), when the dimension d=1, p=q=∞, and ω(y)≡1.
American Psychological Association (APA)
Guo, Huijun& Kou, Junke. 2019. Strong Uniform Convergence Rates of Wavelet Density Estimators with Size-Biased Data. Journal of Function Spaces،Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1174868
Modern Language Association (MLA)
Guo, Huijun& Kou, Junke. Strong Uniform Convergence Rates of Wavelet Density Estimators with Size-Biased Data. Journal of Function Spaces No. 2019 (2019), pp.1-6.
https://search.emarefa.net/detail/BIM-1174868
American Medical Association (AMA)
Guo, Huijun& Kou, Junke. Strong Uniform Convergence Rates of Wavelet Density Estimators with Size-Biased Data. Journal of Function Spaces. 2019. Vol. 2019, no. 2019, pp.1-6.
https://search.emarefa.net/detail/BIM-1174868
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1174868
