Bayes linear statistics : theory and methods
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| Michael Goldstein, David Wooff | ||||
| Wiley Series in Probability and Statistics | ||||
| Wiley | ||||
| 2007 | ||||
| English | ||||
| 539 pages | ||||
| 3.57 MB | ||||
[tab] [content title="Description"]Bayesian methods combine information available from data with any prior information available from expert knowledge. The Bayes linear approach follows this path, offering a quantitative structure for expressing beliefs, and systematic methods for adjusting these beliefs, given observational data. The methodology differs from the full Bayesian methodology in that it establishes simpler approaches to belief specification and analysis based around expectation judgements. Bayes Linear Statistics presents an authoritative account of this approach, explaining the foundations, theory, methodology, and practicalities of this important field. [/content] [content title="Content"] [/content] [content title="About the author"]Michael Goldstein Professor, Statistics DPhil University of Oxford.David A Wooff Department of Mathematical Sciences University of Durham Director of the University of Durham Statistics and Mathematics Consultancy Unit and Professor of Statistics. [/content] [/tab]
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