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Introduction to Statistical Decision Theory: Utility Theory and
Causal Analysis provides the theoretical background to approach
decision theory from a statistical perspective. It covers both
traditional approaches, in terms of value theory and expected
utility theory, and recent developments, in terms of causal
inference. The book is specifically designed to appeal to students
and researchers that intend to acquire a knowledge of statistical
science based on decision theory. Features Covers approaches for
making decisions under certainty, risk, and uncertainty Illustrates
expected utility theory and its extensions Describes approaches to
elicit the utility function Reviews classical and Bayesian
approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision
theory
Introduction to Statistical Decision Theory: Utility Theory and
Causal Analysis provides the theoretical background to approach
decision theory from a statistical perspective. It covers both
traditional approaches, in terms of value theory and expected
utility theory, and recent developments, in terms of causal
inference. The book is specifically designed to appeal to students
and researchers that intend to acquire a knowledge of statistical
science based on decision theory. Features Covers approaches for
making decisions under certainty, risk, and uncertainty Illustrates
expected utility theory and its extensions Describes approaches to
elicit the utility function Reviews classical and Bayesian
approaches to statistical inference based on decision theory
Discusses the role of causal analysis in statistical decision
theory
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