An Introduction to Bayesian Analysis
Theory and Methods
Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta - Collection Springer texts in statistics
Résumé
This book is a contemporary introduction to theory, methods and computation in Bayesian Analysis. It focuses on topics that have stood the test of time and emerging areas such as reference priors, objective Bayes testing, Bayesian model selection and wavelets. No other such book is available in the market.
Written for: Researchers, graduate students
Sommaire
- Statistical preliminaries
- Bayesian inference and decision theory
- Utility, prior, and Bayesian robustness
- Large sample methods
- Choice of priors for low-dimensional parameters
- Hypothesis testing and model selection
- Bayesian computations
- Some common problems in inference
- High-dimensional problems
- Some applications
- A Common statistical densities
- B Birnbaum's theorem on likelihood principle
- C Coherence
- D Microarray
- E Bayes sufficiency
Caractéristiques techniques
| PAPIER | |
| Éditeur(s) | Springer |
| Auteur(s) | Jayanta K. Ghosh, Mohan Delampady, Tapas Samanta |
| Collection | Springer texts in statistics |
| Parution | 31/03/2004 |
| Nb. de pages | 365 |
| Format | 16 x 24 |
| Couverture | Relié |
| Poids | 635g |
| Intérieur | Noir et Blanc |
| EAN13 | 9780387400846 |
| ISBN13 | 978-0-387-40084-6 |
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