Introduction to Statistical Analysis of Random Arrays

AvV. L. Girko

Inbunden, Engelska, 1998

6 279 kr

Beställningsvara. Skickas inom 5-8 vardagar. Fri frakt över 249 kr.

Beskrivning

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

Produktinformation

Utgivningsdatum:1998-12-01
Mått:170 x 240 x 43 mm
Vikt:1 342 g
Format:Inbunden
Språk:Engelska
Antal sidor:697
Upplaga:98001
Förlag:De Gruyter
ISBN:9783110354775

Utforska kategorier

Heminredning inom Hem och Trädgård
Matematisk statistik inom Naturvetenskap och teknik
Algebra inom Naturvetenskap och teknik

Innehållsförteckning

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<1 -- Chapter 13. The First Spacing Law for random symmetric matrices -- Chapter 14. Ten years of General Statistical Analysis (The main G-estimators of General Statistical Analysis) -- References -- Index