Data Analysis: A Bayesian Tutorial 2nd Ed
Devinderjit / Skilling Sivia
Résumé
This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design.
The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Oxford |
| Auteur(s) | Devinderjit / Skilling Sivia |
| Parution | 31/05/2006 |
| Nb. de pages | 256 |
| EAN13 | 9780198568322 |
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