Table of Contents

Foundations.

Generalisations.

Modelling.

Inference.

Remodelling.

Appendices.

References.

Indexes.

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

Reviews

"an excellent primary source for those who wish to learn about thelearning and decision process in a situation of uncertainty..."(Measurement Science Technology, February 2001)

"an ideal source for all students and researchers in statisticsmathematics, decision analysis, economic and business studies andall branches of science and engineering who wish to further theirunderstanding of Bayesian statistics." (Zentralblatt Fur Didaktikder Mathematik)

"...Bayesians will find it indispensable: non-Bayesians will find,and enjoy, much thought-provoking material to challenge theirorthodoxy...." (The Statistician, Vol.51, No.2, 2002)