BAYESIAN INFERENCE
Edward Elgar Publishing
Published on 1. January 1995
Book
Hardback
800 pages
978-1-85278-668-7 (ISBN)
Description
This two volume set is a collection of 30 classic papers presenting ideas which have now become standard in the field of Bayesian inference. Topics covered include the central field of statistical inference as well as applications to areas of probability theory, information theory, utility theory and computational theory. It is organized into seven sections: foundations, information theory and prior distributions; robustness and outliers; hierarchical, multivariate and non-parametric models; asymptotics; computations and Monte Carlo methods; and Bayesian econometrics.
More details
Series
Language
English
Place of publication
Cheltenham
United Kingdom
Target group
College/higher education
Professional and scholarly
Dimensions
Height: 244 mm
Width: 169 mm
ISBN-13
978-1-85278-668-7 (9781852786687)
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Schweitzer Classification
Persons
Edited by Nicholas G. Polson, Assistant Professor of Statistics and George C. Tiao, W. Allen Wallis Professor of Statistics, University of Chicago, US
Content
Volume I: information theory and prior distributions; robustness and outliers. Volume II: hierarchical, multivariate and non-parametric models; asymptotics; computation via Monte Carlo methods; Bayesian econometrics.