Book contents
- Frontmatter
- Contents
- Preface
- List of Symbols
- Part I Classical Random Matrix Theory
- Part II Sums and Products of Random Matrices
- Part III Applications
- 15 Addition and Multiplication: Recipes and Examples
- 16 Products of Many Random Matrices
- 17 Sample Covariance Matrices
- 18 Bayesian Estimation
- 19 Eigenvector Overlaps and Rotationally Invariant Estimators
- 20 Applications to Finance
- Appendix Mathematical Tools
- Index
16 - Products of Many Random Matrices
from Part III - Applications
Published online by Cambridge University Press: 12 November 2020
- Frontmatter
- Contents
- Preface
- List of Symbols
- Part I Classical Random Matrix Theory
- Part II Sums and Products of Random Matrices
- Part III Applications
- 15 Addition and Multiplication: Recipes and Examples
- 16 Products of Many Random Matrices
- 17 Sample Covariance Matrices
- 18 Bayesian Estimation
- 19 Eigenvector Overlaps and Rotationally Invariant Estimators
- 20 Applications to Finance
- Appendix Mathematical Tools
- Index
Summary
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- A First Course in Random Matrix Theoryfor Physicists, Engineers and Data Scientists, pp. 257 - 266Publisher: Cambridge University PressPrint publication year: 2020