Abstract
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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2010 Springer Science+Business Media, LLC
About this chapter
Cite this chapter
Bai, Z., Silverstein, J.W. (2010). CLT for Linear Spectral Statistics. In: Spectral Analysis of Large Dimensional Random Matrices. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4419-0661-8_9
Download citation
DOI: https://doi.org/10.1007/978-1-4419-0661-8_9
Published:
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-0660-1
Online ISBN: 978-1-4419-0661-8
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)