Please use this identifier to cite or link to this item: https://doi.org/10.1214/10-AOS833
Title: Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
Authors: Jing, B.-Y.
Pan, G.
Shao, Q.-M.
Zhou, W. 
Keywords: Nonparametric estimate
Sample covariance matrices
Stieltjes transform
Issue Date: Dec-2010
Source: Jing, B.-Y., Pan, G., Shao, Q.-M., Zhou, W. (2010-12). Nonparametric estimate of spectral density functions of sample covariance matrices: A first step. Annals of Statistics 38 (6) : 3724-3750. ScholarBank@NUS Repository. https://doi.org/10.1214/10-AOS833
Abstract: The density function of the limiting spectral distribution of general sample covariance matrices is usually unknown.We propose to use kernel estimators which are proved to be consistent. A simulation study is also conducted to show the performance of the estimators. © Institute of Mathematical Statistics, 2010.
Source Title: Annals of Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/105240
ISSN: 00905364
DOI: 10.1214/10-AOS833
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