About this Item
Hardcover. 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. The text provides a thorough coverage of Bayes linear analysis, from the development of the basic language to the collection of algebraic results needed for efficient implementation, with detailed practical examples. The book covers: The importance of partial prior specifications for complex problems where it is difficult to supply a meaningful full prior probability specification.Simple ways to use partial prior specifications to adjust beliefs, given observations.Interpretative and diagnostic tools to display the implications of collections of belief statements, and to make stringent comparisons between expected and actual observations.General approaches to statistical modelling based upon partial exchangeability judgements.Bayes linear graphical models to represent and display partial belief specifications, organize computations, and display the results of analyses. Bayes Linear Statistics is essential reading for all statisticians concerned with the theory and practice of Bayesian methods. There is an accompanying website hosting free software and guides to the calculations within the book. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9780470015629
Bibliographic Details
Title: Bayes Linear Statistics (Hardcover)
Publisher: John Wiley & Sons Inc, New York
Publication Date: 2007
Binding: Hardcover
Condition: new
Edition: 1st Edition
About this title
The text provides a thorough coverage of Bayes linear analysis, from the development of the basic language to the collection of algebraic results needed for efficient implementation, with detailed practical examples.
The book covers:
Bayes Linear Statistics is essential reading for all statisticians concerned with the theory and practice of Bayesian methods. There is an accompanying website hosting free software and guides to the calculations within the book.
David Wooff, Director of Statistics & Mathematics Consultancy Unit and Senior Lecturer in Statistics, Department of Mathematical Sciences, University of Durham
David Wooff has been involved in a long collaboration for over 20 years with Michael Goldstein and others on developing Bayes linear methods, his primary research interest being the general development and application of Bayes linear methodology.
"About this title" may belong to another edition of this title.
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