CLT for Linear Spectral Statistics

  • Zhidong Bai
  • Jack W. Silverstein
Part of the Springer Series in Statistics book series (SSS)


As mentioned in the introduction, many important statistics in multivariate analysis can be written as functionals of the ESD of some random matrices. The strong consistency of the ESD with LSD is not enough for more efficient statistical inferences, such as the test of hypotheses, confidence regions, etc. In this chapter, we shall introduce some results on deeper properties of the convergence of the ESD of large dimensional random matrices.


Covariance Function Sample Covariance Matrix Wigner Matrice Wishart Matrix Sample Covariance Matrice 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.School of Mathematics and Statistics KLAS MOE Northeast Normal UniversityChangchunChina
  2. 2.Department of Statistics and Applied ProbabilityNational University of SingaporeSingaporeSingapore
  3. 3.Department of MathematicsNorth Carolina State UniversityRaleighUS

Personalised recommendations