Chapter 1 Introduction / Rodrigo A. Collazo -- chapter 2 Bayesian inference using graphs / Rodrigo A. Collazo -- chapter 3 The Chain Event Graph / Rodrigo A. Collazo -- chapter 4 Reasoning with a CEG / Rodrigo A. Collazo -- chapter 5 Estimation and propagation on a given CEG / Rodrigo A. Collazo -- chapter 6 Model selection for CEGs / Rodrigo A. Collazo -- chapter 7 How to model with a CEG.? A real?world application / Rodrigo A. Collazo -- chapter 8 Causal inference using CEGs / Rodrigo A. Collazo
Summary
"A chain event graph (CEG) is an important generalization of the Bayesian Network (BN). BNs have been extremely useful for modeling discrete processes. However, they are not appropriate for all applications. Over the past six years or so, teams of researchers led by Jim Smith have established a strong theoretical underpinning for CEGs. This book systematically and transparently presents the scope and promise of this emerging class of models, together with its underpinning methodology, to a wide audience."--Provided by publisher
