Book contents
- Frontmatter
- Dedication
- Contents
- Notation
- Preface
- 1 Introduction
- 2 Limiting Spectral Distributions
- 3 CLT for Linear Spectral Statistics
- 4 The Generalised Variance and Multiple Correlation Coefficient
- 5 The T2-Statistic
- 6 Classification of Data
- 7 Testing the General Linear Hypothesis
- 8 Testing Independence of Sets of Variates
- 9 Testing Hypotheses of Equality of Covariance Matrices
- 10 Estimation of the Population Spectral Distribution
- 11 Large-Dimensional Spiked Population Models
- 12 Efficient Optimisation of a Large Financial Portfolio
- Appendix A Curvilinear Integrals
- Appendix B Eigenvalue Inequalities
- References
- Index
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9 - Testing Hypotheses of Equality of Covariance Matrices
Book contents
- Frontmatter
- Dedication
- Contents
- Notation
- Preface
- 1 Introduction
- 2 Limiting Spectral Distributions
- 3 CLT for Linear Spectral Statistics
- 4 The Generalised Variance and Multiple Correlation Coefficient
- 5 The T2-Statistic
- 6 Classification of Data
- 7 Testing the General Linear Hypothesis
- 8 Testing Independence of Sets of Variates
- 9 Testing Hypotheses of Equality of Covariance Matrices
- 10 Estimation of the Population Spectral Distribution
- 11 Large-Dimensional Spiked Population Models
- 12 Efficient Optimisation of a Large Financial Portfolio
- Appendix A Curvilinear Integrals
- Appendix B Eigenvalue Inequalities
- References
- Index
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- Publisher: Cambridge University PressPrint publication year: 2015
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