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Chain event graphs

By: Collazo, Rodrigo A.
Contributor(s): Gorgen, Christiane [Co author] | Smith, Jim Q [Co author].
Material type: materialTypeLabelBookSeries: Chapman and Hall/CRC computer science and data analysis series. Publisher: Florida CRC Press 2018Description: xx, 233p. With index.ISBN: 9781498729604.Subject(s): Mathematical statistics--graphic methods | Trees--graph theory | Bayesian statistical decision theoryDDC classification: 519.542 Summary: 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
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Item type Current location Item location Collection Call number Status Date due Barcode
Books Vikram Sarabhai Library
General Stacks
Slot 1675 (2 Floor, East Wing) Non-fiction 519.542 C6C4 (Browse shelf) Not for Issue 199224

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

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

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