Bayesian Statistics
Principles, Models and Applications
S. James Press(Author)
Wiley (Publisher)
Published on 10. May 1989
Book
Hardback
256 pages
978-0-471-63729-5 (ISBN)
Article exhausted; check for reprint
Description
An introduction to Bayesian statistics, with emphasis on interpretation of theory, and application of Bayesian ideas to practical problems, is provided in this volume. The first part covers basic issues and principles, such as subjective probability, Bayesian inference and decision making, the likelihood principle, predictivism, and numerical methods of approximating posterior distributions, and includes a listing of Bayesian computer programs. The second part is devoted to models and applications, including univariate and multivariate regression models, the general linear model, Bayesian classification and discrimination, and a case study of how disputed authorship of some of the Federalist Papers was resolved via Bayesian analysis. The book also includes biographical material on Thomas Bayes, and a reproduction of Bayes's original essay.
More details
Series
Language
English
Place of publication
New York
United States
Publishing group
John Wiley and Sons Ltd
Target group
College/higher education
Illustrations
bibliography, index
Dimensions
Height: 236 mm
Width: 158 mm
Weight
486 gr
ISBN-13
978-0-471-63729-5 (9780471637295)
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Schweitzer Classification
Other editions
New editions

Book
12/2002
2nd Edition
Wiley
€180.50
Shipment within 10-20 days
Content
Part 1 Theory: foundations; principles; approximations, numerical methods, and computer programs; assessment of multivariate prior distributions: assessing the probability of nuclear war. Part 2 Models and applications: Bayesian inference in regression; Bayesian multivariate analysis of variance and covariance; Bayesian inference in classification and discrimination; a case study in applied Bayesian inference. Appendices: an encyclopedia article entitled "Bayes, Thomas"; a biographical note on Bayes's essay; the letter of submission of Bayes's essay to the Royal Society; Bayes's original essay.