Introduction to Statistical Decision Theory: Utility Theory and Causal Analysis
About this ebook
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
About the author
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.
