Bayesian Theory

José M. Bernardo, Adrian F. M. Smith

ISBN 10: 047149464X / ISBN 13: 9780471494645

Published by John Wiley and Sons Inc, US, 2000

About this Item

This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called prior ignorance . The work is written from the authors s committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. The level of mathematics used is such that most material is accessible to readers with knowledge of advanced calculus. In particular, no knowledge of abstract measure theory is assumed, and the emphasis throughout is on statistical concepts rather than rigorous mathematics. The book will be an ideal source for all students and researchers in statistics, mathematics, decision analysis, economic and business studies, and all branches of science and engineering, who wish to further their understanding of Bayesian statistics.

Seller Inventory # LU-9780471494645

Bibliographic Details

• Title: Bayesian Theory
• Publisher: John Wiley and Sons Inc, US
• Publication Date: 2000
• Language: English
• ISBN 10: 047149464X
• ISBN 13: 9780471494645
• Binding: Paperback
• Edition: 1st.
• Condition: New
• Dimensions: 15.35W x 3.52H x 23.2D centimeters 15.35 centimeters width by 3.52 centimeters height by 23.2 centimeters depth
• Weight: 868 grams

About this title

Synopsis

This highly acclaimed text, now available in paperback, provides a thorough account of key concepts and theoretical results, with particular emphasis on viewing statistical inference as a special case of decision theory. Information-theoretic concepts play a central role in the development of the theory, which provides, in particular, a detailed discussion of the problem of specification of so-called prior ignorance . The work is written from the authors s committed Bayesian perspective, but an overview of non-Bayesian theories is also provided, and each chapter contains a wide-ranging critical re-examination of controversial issues. The level of mathematics used is such that most material is accessible to readers with knowledge of advanced calculus. In particular, no knowledge of abstract measure theory is assumed, and the emphasis throughout is on statistical concepts rather than rigorous mathematics. The book will be an ideal source for all students and researchers in statistics, mathematics, decision analysis, economic and business studies, and all branches of science and engineering, who wish to further their understanding of Bayesian statistics

About the Author

About the Authors Jose M. Bernardo received his PhD from University College London and has subsequently been at the University of Valencia, Spain, where he is currently Professor of Statistics and special scientific advisor to the Governor of the State of Valencia. Adrian F. M. Smith received his PhD from University College London and is currently at Imperial College London, where he is Professor of Statistics and Head of the Department of Mathematics