Bayes Linear Statistics
Theory & Methods
Chapter One
The Bayes linear approach
The subject of this book is the qualitative and quantitative analysis of our beliefs,
with particular emphasis on the combination of beliefs and data in statistical analysis.
In particular, we will cover:
(i) the importance of partial prior specifications for problems which are too complex
to allow us to make meaningful full prior specifications;
(ii) simple ways to use our partial prior specifications to adjust our beliefs given
observations;
(iii) interpretative and diagnostic tools that help us, first, to understand the implications
of our collections of belief statements and, second, to make stringent
comparisons between what we expect to observe and what we actually observe;
(iv) general approaches to statistical modelling based upon partial exchangeability
judgements;
(v) partial graphical models to represent our beliefs, organize our computations
and display the results of our analysis.
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