Description
Introduction to Statistical Decision Theory
Utility Theory and Causal Analysis
Authors: Bacci Silvia, Chiandotto Bruno
Language: EnglishSubjects for Introduction to Statistical Decision Theory:
Keywords
Rank Dependent Utility Theory; Maximum Surface Wind Speed; Hurwicz’s Criterion; Expected Utility Principle; Expected Utility Theory; Decision Table; Criterion Decision Methods; Prior Information; Classical Decision Theory; Tv User; Recursive SEM; Standard Gamble Methods; Tv Device; CE; Recursive Path Models; Descriptive Decision Theory; European Customer Satisfaction Index; Normative Decision Theory; Causal Decision Theory; Informational Background; Max Min Criterion; Independence Axiom; Utility Function; Decision Function; Swedish Customer Satisfaction Barometer
Publication date: 06-2021
· 15.6x23.4 cm · Paperback
174.18 €
In Print (Delivery period: 14 days).
Add to cart the book of Bacci Silvia, Chiandotto BrunoPublication date: 07-2019
· 15.6x23.4 cm · Hardback
Description
/li>Contents
/li>Biography
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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
1. Statistics and decisions 2. Probability and statistical inference 3. Utility theory 4. Utility function elicitation 5. Classical and bayesian statistical decision theory 6. Statistics, causality, and decisions
Silvia Bacci is Assistant Professor of Statistics at the Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence (Italy). Her research interests are addressed to statistical decision theory, with focus on utility theory, and latent variable models, with focus on item response theory models, latent class models, and models for longitudinal and multilevel data.
Bruno Chiandotto is adjunct Full Professor of Statistics at the Department of Statistics, Computer Science and Applications "G. Parenti", University of Florence (Italy). He is mainly interested in the definition and estimation of linear and nonlinear statistical models, multivariate data analysis, customer satisfaction, causal analysis, statistical decision theory and utility theory. A large part of his research activity has been carried out under projects funded by international, national and local institutions.
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