Computational statistics
Computational inference has taken its place alongside asymptotic inference and exact techniques in the standard collection of statistical methods. Computational inference is based on an approach to statistical methods that uses modern computational power to simulate distributional properties of esti...
Enregistré dans:
| Auteur principal: | |
|---|---|
| Format: | Livre numérique |
| Langue: | Anglais |
| Publié: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Collection: | Statistics and Computing
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| Sujets: | |
| Accès en ligne: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Note: |
Description d'après consultation du 15 décembre 2011 Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Computational statistics, James E. Gentle, New York, Springer, 2009, 1 vol. (XXI-727 p.), Statistics and computing, 978-0-387-98143-7 |
Table des matières:
- Preliminaries Mathematical and Statistical Preliminaries Statistical Computing Computer Storage and Arithmetic Algorithms and Programming Approximation of Functions and Numerical Quadrature Numerical Linear Algebra Solution of Nonlinear Equations and Optimization Generation of Random Numbers Methods of Computational Statistics Graphical Methods in Computational Statistics Tools for Identification of Structure in Data Estimation of Functions Monte Carlo Methods for Statistical Inference Data Randomization, Partitioning, and Augmentation Bootstrap Methods Exploring Data Density and Relationships Estimation of Probability Density Functions Using Parametric Models Nonparametric Estimation of Probability Density Functions Statistical Learning and Data Mining Statistical Models of Dependencies