Nonparametric estimate of spectral density functions of sample covariance matrices: A first step
Statistics Theory
2012-11-15 v1 Statistics Theory
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.
Keywords
Cite
@article{arxiv.1211.3230,
title = {Nonparametric estimate of spectral density functions of sample covariance matrices: A first step},
author = {Bing-Yi Jing and Guangming Pan and Qi-Man Shao and Wang Zhou},
journal= {arXiv preprint arXiv:1211.3230},
year = {2012}
}
Comments
Published in at http://dx.doi.org/10.1214/10-AOS833 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)