Introduction to statistical decision theory : utility theory and causal analysis / Silvia Bacci, Bruno Chiandotto.

By: Bacci, Silvia [author.]Contributor(s): Chiandotto, Bruno [author.]Material type: TextTextPublisher: Boca Raton, FL : CRC Press, 2020Copyright date: ©2020Description: 1 online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9781315112220; 1315112221; 9781351621380; 1351621386; 9781351621397; 1351621394; 9781351621373; 1351621378Subject(s): Statistical decision | Mathematical statistics | Statistics | MATHEMATICS / Probability & Statistics / GeneralDDC classification: 519.5 LOC classification: QA279.4 | .B33 2020Online resources: Taylor & Francis | OCLC metadata license agreement Summary: 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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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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