Abstract
This chapter differs from later chapters in scope, because Bayesian analysis is an essentially self-contained paradigm for statistics. (Later chapters will, for the most part, deal with special topics within frequentist decision theory.) In order to provide a satisfactory perspective on Bayesian analysis, we will discuss Bayesian inference along with Bayesian decision theory. Before beginning the study, however, we briefly discuss the seven major arguments that can be given in support of Bayesian analysis. (Later chapters will similarly begin with a discussion of justifications.) Some of these arguments will not be completely understandable initially, but are best placed together for reference purposes.
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© 1985 Springer Science+Business Media New York
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Berger, J.O. (1985). Bayesian Analysis. In: Statistical Decision Theory and Bayesian Analysis. Springer Series in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4286-2_4
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DOI: https://doi.org/10.1007/978-1-4757-4286-2_4
Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4419-3074-3
Online ISBN: 978-1-4757-4286-2
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