Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
Jing, Bing-Yi ; Pan, Guangming ; Shao, Qi-Man ; Zhou, Wang
Ann. Statist., Tome 38 (2010) no. 1, p. 3724-3750 / Harvested from Project Euclid
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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.
Publié le : 2010-12-15
Classification:  Sample covariance matrices,  Stieltjes transform,  nonparametric estimate,  15A52,  60F15,  62E20,  60F17 
@article{1291126971,
     author = {Jing, Bing-Yi and Pan, Guangming and Shao, Qi-Man and Zhou, Wang},
     title = {Nonparametric estimate of spectral density functions of sample covariance matrices: A first step},
     journal = {Ann. Statist.},
     volume = {38},
     number = {1},
     year = {2010},
     pages = { 3724-3750},
     language = {en},
     url = {http://dml.mathdoc.fr/item/1291126971}
}

Jing, Bing-Yi; Pan, Guangming; Shao, Qi-Man; Zhou, Wang. Nonparametric estimate of spectral density functions of sample covariance matrices: A first step. Ann. Statist., Tome 38 (2010) no. 1, pp.  3724-3750. http://gdmltest.u-ga.fr/item/1291126971/