Bayes Linear Statistics

This book explains the foundations, theory, methodology, mathematics & practicalities of what is generally termed the Bayes linear approach. It explains the main concepts, and illustrates them with a number of practical examples. It begins by carefully developing the basic language of Bayes linear analysis, describing the fundamental operations of belief adjustment and partial adjustment and their interpretations. It describes the role of exchangeability, and discusses more general ways of analyzing beliefs via general belief transforms, and shows how the Bayes linear approach may be used to analyse statistical examples of various degrees of complexity. The twin roles of Bayes linear influence diagrams are discussed, and it concludes by collecting together all the algebraic results needed for efficient implementation of the Bayes linear approach.