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Bayes linear statistics : theory and methods
























Bayes linear statistics : theory and methods


Author(s):
Michael Goldstein, David Wooff



Collection:
Wiley Series in Probability and Statistics


Publisher:
Wiley


Year:
2007


Language:
English


Pages:
539 pages


Size:
3.57 MB


Extension:
PDF





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[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.
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[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.

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