An Introduction to Bayesian Analysis Theory and Methods
By way of important applications the book presents microarrays, nonparametric regression via wavelets as well as DMA mixtures of normals, and spatial analysis with illustrations using simulated and real data. Theoretical topics at the cutting edge include high-dimensional model selection and Intrins...
| Main Authors: | , , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2006, 2006
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| Edition: | 1st ed. 2006 |
| Series: | Springer Texts in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 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