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A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working.
Like the De Groot winning first edition, the second edition of Principles of Uncertainty is an accessible, comprehensive guide to the theory of Bayesian Statistics written in an appealing, inviting style, and packed with interesting examples.
A fair question to ask of an advocate of subjective Bayesianism (which the author is) is "how would you model uncertainty?" In this book, the author writes about how he has done it using real problems from the past, and offers additional comments about the context in which he was working.
This important collection of essays is a synthesis of foundational studies in Bayesian decision theory and statistics. The collection explores how the norms for Bayesian decision making should apply in settings with more than one rational decision maker and then tracing out some of the consequences of this turn for Bayesian statistics.
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