An Introduction to Statistical Analysis of Random Arrays - Couverture rigide

Girko, V. L.

9783110354775: An Introduction to Statistical Analysis of Random Arrays

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ISBN 10 : 3110354772 ISBN 13 : 9783110354775

Editeur : De Gruyter, 1998

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No detailed description available for "An Introduction to Statistical Analysis of Random Arrays".

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�diteur: De Gruyter
Date d'�dition: 1998
Langue: anglais
ISBN 10: 3110354772
ISBN 13: 9783110354775
Reliure: Reli�
Nombre de pages: 699
Coordonn�es du fabricant: productsafety@degruyterbrill.com
productsafety@degruyterbrill.com

Paul-Lincke-Ufer 34
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Allemagne

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An Introduction to Statistical Analysis of Random Arrays

V. L. Girko

Edit� par De Gruyter, 1998

ISBN 10 : 3110354772 ISBN 13 : 9783110354775

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Gebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. No detailed description available for An Introduction to Statistical Analysis of Random Arrays .Frontmatter -- CONTENTS -- List of basic notations and assumptions -- Preface and some historical remarks -- Chapter 1. Introduction to the theory of sample. N� de r�f. du vendeur 448704025

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An Introduction to Statistical Analysis of Random Arrays

V. L. Girko

Edit� par De Gruyter Dez 1998, 1998

ISBN 10 : 3110354772 ISBN 13 : 9783110354775

Neuf Buch

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Frontmatter -- CONTENTS -- List of basic notations and assumptions -- Preface and some historical remarks -- Chapter 1. Introduction to the theory of sample matrices of fixed dimension -- Chapter 2. Canonical equations -- Chapter 3. The First Law for the eigenvalues and eigenvectors of random symmetric matrices -- Chapter 4. The Second Law for the singular values and eigenvectors of random matrices. Inequalities for the spectral radius of large random matrices -- Chapter 5. The Third Law for the eigenvalues and eigenvectors of empirical covariance matrices -- Chapter 6. The first proof of the Strong Circular Law -- Chapter 7. Strong Law for normalized spectral functions of nonselfadjoint random matrices with independent row vectors and simple rigorous proof of the Strong Circular Law -- Chapter 8. Rigorous proof of the Strong Elliptic Law -- Chapter 9. The Circular and Uniform Laws for eigenvalues of random nonsymmetric complex matrices with independent entries -- Chapter 10. Strong V-Law for eigenvalues of nonsymmetric random matrices -- Chapter 11. Convergence rate of the expected spectral functions of symmetric random matrices is equal to 0(n-1/2) -- Chapter 12. Convergence rate of expected spectral functions of the sample covariance matrix m'(n) is equal to 0(n-1/2) under the condition m'n-1 c 700 pp. Englisch. N� de r�f. du vendeur 9783110354775

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An Introduction to Statistical Analysis of Random Arrays

V. L. Girko

Edit� par de Gruyter, 1998

ISBN 10 : 3110354772 ISBN 13 : 9783110354775

Neuf Couverture rigide

impression � la demande

Vendeur : PBShop.store UK, Fairford, GLOS, Royaume-Uni

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HRD. Etat : New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. N� de r�f. du vendeur L1-9783110354775

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An Introduction to Statistical Analysis of Random Arrays

V. L. Girko

Edit� par De Gruyter, De Gruyter Dez 1998, 1998

ISBN 10 : 3110354772 ISBN 13 : 9783110354775

Neuf Buch

Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne

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Buch. Etat : Neu. Neuware -Frontmatter -- CONTENTS -- List of basic notations and assumptions -- Preface and some historical remarks -- Chapter 1. Introduction to the theory of sample matrices of fixed dimension -- Chapter 2. Canonical equations -- Chapter 3. The First Law for the eigenvalues and eigenvectors of random symmetric matrices -- Chapter 4. The Second Law for the singular values and eigenvectors of random matrices. Inequalities for the spectral radius of large random matrices -- Chapter 5. The Third Law for the eigenvalues and eigenvectors of empirical covariance matrices -- Chapter 6. The first proof of the Strong Circular Law -- Chapter 7. Strong Law for normalized spectral functions of nonselfadjoint random matrices with independent row vectors and simple rigorous proof of the Strong Circular Law -- Chapter 8. Rigorous proof of the Strong Elliptic Law -- Chapter 9. The Circular and Uniform Laws for eigenvalues of random nonsymmetric complex matrices with independent entries -- Chapter 10. Strong V-Law for eigenvalues of nonsymmetric random matrices -- Chapter 11. Convergence rate of the expected spectral functions of symmetric random matrices is equal to 0(n-1/2) -- Chapter 12. Convergence rate of expected spectral functions of the sample covariance matrix m'(n) is equal to 0(n-1/2) under the condition m'n-1 cWalter de Gruyter GmbH, Genthiner Strasse 13, 10785 Berlin 700 pp. Englisch. N� de r�f. du vendeur 9783110354775

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An Introduction to Statistical Analysis of Random Arrays

V. L. Girko

Edit� par De Gruyter, 1998

ISBN 10 : 3110354772 ISBN 13 : 9783110354775

Neuf Couverture rigide

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Frontmatter -- CONTENTS -- List of basic notations and assumptions -- Preface and some historical remarks -- Chapter 1. Introduction to the theory of sample matrices of fixed dimension -- Chapter 2. Canonical equations -- Chapter 3. The First Law for the eigenvalues and eigenvectors of random symmetric matrices -- Chapter 4. The Second Law for the singular values and eigenvectors of random matrices. Inequalities for the spectral radius of large random matrices -- Chapter 5. The Third Law for the eigenvalues and eigenvectors of empirical covariance matrices -- Chapter 6. The first proof of the Strong Circular Law -- Chapter 7. Strong Law for normalized spectral functions of nonselfadjoint random matrices with independent row vectors and simple rigorous proof of the Strong Circular Law -- Chapter 8. Rigorous proof of the Strong Elliptic Law -- Chapter 9. The Circular and Uniform Laws for eigenvalues of random nonsymmetric complex matrices with independent entries -- Chapter 10. Strong V-Law for eigenvalues of nonsymmetric random matrices -- Chapter 11. Convergence rate of the expected spectral functions of symmetric random matrices is equal to 0(n-1/2) -- Chapter 12. Convergence rate of expected spectral functions of the sample covariance matrix m'(n) is equal to 0(n-1/2) under the condition m'n-1 c. N� de r�f. du vendeur 9783110354775

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