Introduction to Bayesian Scientific Computing : Ten Lectures on Subjective Computing
A combination of the concepts subjective or Bayesian statistics and scientific computing, the book provides an integrated view across numerical linear algebra and computational statistics. Inverse problems act as the bridge between these two fields where the goal is to estimate an unknown parameter...
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| Auteurs principaux: | , |
|---|---|
| 格式: | Livre numérique |
| 語言: | Anglais |
| 出版: |
New York, NY :
Springer New York
2007.
Cham : Springer Nature |
| 叢編: | Surveys and Tutorials in the Applied Mathematical Sciences
2 |
| 主題: | |
| 在線閱讀: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| 提示: |
Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Introduction to Bayesian scientific computing, ten lectures on subjective computing, Daniela Cavetti, Erkki Somersalo, New York, Springer Science, 2007, 1 vol. (XIV-202 p.), Surveys and tutorials in the applied mathematical sciences, 978-0-387-73393-7 • Analysis, 1, Konrad Königsberger, 1990, Berlin, Springer, 1 vol. (XI, 360 p.), 3-540-52006-6 |
書本目錄:
- Inverse problems and subjective computing
- Basic problem of statistical inference
- The praise of ignorance: randomness as lack of information
- Basic problem in numerical linear algebra
- Sampling: first encounter
- Statistically inspired preconditioners
- Conditional Gaussian densities and predictive envelopes
- More applications of the Gaussian conditioning
- Sampling: the real thing
- Wrapping up: hypermodels, dynamic priorconditioners and Bayesian learning.