Numerical Analysis for Statisticians
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 equips students to craft their own software and to understand the advantages and disadvantages of...
Guardat en:
| Autor principal: | |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Edició: | 2nd ed. 2010. |
| Col·lecció: | Statistics and Computing
|
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Numerical analysis for statisticians, Kenneth Lange, 2nd edition, 2010, New York, Springer, 1 vol. (XX-600 p.), Statistics and computing, 978-1-4419-5944-7 |
Taula de continguts:
- Recurrence Relations Power Series Expansions Continued Fraction Expansions Asymptotic Expansions Solution of Nonlinear Equations Vector and Matrix Norms Linear Regression and Matrix Inversion Eigenvalues and Eigenvectors Singular Value Decomposition Splines Optimization Theory The MM Algorithm The EM Algorithm Newton s Method and Scoring Local and Global Convergence Advanced Optimization Topics Concrete Hilbert Spaces Quadrature Methods The Fourier Transform The Finite Fourier Transform Wavelets Generating Random Deviates Independent Monte Carlo Permutation Tests and the Bootstrap Finite-State Markov Chains Markov Chain Monte Carlo Advanced Topics in MCMC