Chain event graphs
Collazo, Rodrigo A.
creator
Gorgen, Christiane
Co author
Smith, Jim Q.
Co author
text
Florida
CRC Press
2018
monographic
| 0
xx, 233p. With index
Written by some major contributors to the development of this class of graphical models, Chain Event Graphs introduces a viable and straightforward new tool for statistical inference, model selection and learning techniques. The book extends established technologies used in the study of discrete Bayesian Networks so that they apply in a much more general setting As the first book on Chain Event Graphs, this monograph is expected to become a landmark work on the use of event trees and coloured probability trees in statistics, and to lead to the increased use of such tree models to describe hypotheses about how events might unfold.
Features:
introduces a new and exciting discrete graphical model based on an event tree
focusses on illustrating inferential techniques, making its methodology accessible to a very broad audience and, most importantly, to practitioners
illustrated by a wide range of examples, encompassing important present and future applications
includes exercises to test comprehension and can easily be used as a course book
introduces relevant software packages
https://www.crcpress.com/Chain-Event-Graphs/Collazo-Goergen-Smith/p/book/9781498729604
Table of Contents
1.Introduction
2.Bayesian inference using graphs
3.The Chain Event Graph
4.Reasoning with a CEG
5.Estimation and propagation on a given CEG
6.Model selection for CEGs
7.How to model with a CEG: a real-world application
8.Causal inference using CEGs
Mathematical statistics--graphic methods
Trees--graph theory
Bayesian statistical decision theory
519.542 C6C4
Chapman and Hall/CRC computer science and data analysis series
9781498729604
190429