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Main Title Numerical analysis for statisticians /
Author Lange, Kenneth.
Publisher Springer,
Year Published 1999
OCLC Number 38842134
ISBN 0387949798; 9780387949796
Subjects Numerical analysis ; Mathematical statistics ; Computational statistics ; Numerische Mathematik--(DE-588)4042805-9 ; Statistik--(DE-588)4056995-0 ; MâETODOS COMPUTACIONAIS (PESQUISA OPERACIONAL) ; Statistique mathématique ; Analyse numérique ; Analyse num erique ; Statistique math ematique ; M ETODOS COMPUTACIONAIS (PESQUISA OPERACIONAL)--larpcal
Internet Access
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Table of contents
Table of contents
Publisher description
Library Call Number Additional Info Location Last
EKBM  QA297.L34 1999 Research Triangle Park Library/RTP, NC 05/07/2004
Collation xv, 356 pages ; 24 cm.
Includes bibliographical references and index.
Contents Notes
Every advance in computer architecture and software tempts statisticians to tackle numerically harder problems. To do so intelligently requires a good working knowledge of numerical analysis. This book is intended to equip students to craft their own software and to understand the advantages and disadvantages of different numerical methods and can serve as a graduate text for either a one- or a two-semester course surveying computational statistics. With a careful selection of topics and appropriate supplementation, it can even be used at the undergraduate level. Because many of the chapters are nearly self-contained, professional statisticians will also find the book useful as a reference. 1. Recurrence Relations -- 2. Power Series Expansions -- 3. Continued Fraction Expansions -- 4. Asymptotic Expansions -- 5. Solution of Nonlinear Equations -- 6. Vector and Matrix Norms -- 7. Linear Regression and Matrix Inversion -- 8. Eigenvalues and Eigenvectors -- 9. Splines -- 10. The EM Algorithm -- 11. Newton's Method and Scoring -- 12. Variations on the EM Theme -- 13. Convergence of Optimization Algorithms -- 14. Constrained Optimization -- 15. Concrete Hilbert Spaces -- 16. Quadrature Methods -- 17. The Fourier Transform -- 18. The Finite Fourier Transform -- 19. Wavelets -- 20. Generating Random Deviates -- 21. Independent Monte Carlo -- 22. Bootstrap Calculations -- 23. Finite-State Markov Chains -- 24. Markov Chain Monte Carlo.