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A First Course in Random Matrix Theory
Buch von Marc Potters (u. a.)
Sprache: Englisch

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Beschreibung
An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.
An intuitive, up-to-date introduction to random matrix theory and free calculus, with real world illustrations and Big Data applications.
Über den Autor
Marc Potters is Chief Investment Officer of CFM, an investment firm based in Paris. Marc maintains strong links with academia and as an expert in Random Matrix Theory, he has taught at UCLA and Sorbonne University. He is co-author of Theory of Financial Risk and Derivative Pricing (Cambridge 2003).
Inhaltsverzeichnis
Preface; Part I. Classical Random Matrix Theory: 1. Deterministic Matrices; 2. Wigner Ensemble and Semi-circle Law; 3. More on Gaussian Matrices; 4. Wishart Ensemble and Marcenko-Pastur Distribution; 5. Joint Distribution of Eigenvalues; 7. The Jacobi Ensemble; Part II. Sums and Products of Random Matrices: 8. Addition of Random Variables and Brownian Motion; 9. Dyson Brownian Motion; 10. Addition of Large Random Matrices; 11. Free Probabilities; 12. Free Random Matrices; 13. The Replica Method; 14. Edge Eigenvalues and Outliers; 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 A. Appendices: Mathematical Tools; List of Symbols; Index.
Details
Erscheinungsjahr: 2020
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108488082
ISBN-10: 1108488080
Sprache: Englisch
Einband: Gebunden
Autor: Potters, Marc
Bouchaud, Jean-Philippe
Hersteller: Cambridge University Press
Maße: 253 x 180 x 27 mm
Von/Mit: Marc Potters (u. a.)
Erscheinungsdatum: 03.12.2020
Gewicht: 0,787 kg
Artikel-ID: 121100108
Über den Autor
Marc Potters is Chief Investment Officer of CFM, an investment firm based in Paris. Marc maintains strong links with academia and as an expert in Random Matrix Theory, he has taught at UCLA and Sorbonne University. He is co-author of Theory of Financial Risk and Derivative Pricing (Cambridge 2003).
Inhaltsverzeichnis
Preface; Part I. Classical Random Matrix Theory: 1. Deterministic Matrices; 2. Wigner Ensemble and Semi-circle Law; 3. More on Gaussian Matrices; 4. Wishart Ensemble and Marcenko-Pastur Distribution; 5. Joint Distribution of Eigenvalues; 7. The Jacobi Ensemble; Part II. Sums and Products of Random Matrices: 8. Addition of Random Variables and Brownian Motion; 9. Dyson Brownian Motion; 10. Addition of Large Random Matrices; 11. Free Probabilities; 12. Free Random Matrices; 13. The Replica Method; 14. Edge Eigenvalues and Outliers; 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 A. Appendices: Mathematical Tools; List of Symbols; Index.
Details
Erscheinungsjahr: 2020
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108488082
ISBN-10: 1108488080
Sprache: Englisch
Einband: Gebunden
Autor: Potters, Marc
Bouchaud, Jean-Philippe
Hersteller: Cambridge University Press
Maße: 253 x 180 x 27 mm
Von/Mit: Marc Potters (u. a.)
Erscheinungsdatum: 03.12.2020
Gewicht: 0,787 kg
Artikel-ID: 121100108
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