Graphical Models

Hardcover | April 30, 1999

bySteffen L. Lauritzen

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The idea of modelling systems using graph theory has its origin in several scientific areas: in statistical physics (the study of large particle systems), in genetics (studying inheritable properties of natural species), and in interactions in contingency tables. The use of graphical models instatistics has increased considerably over recent years and the theory has been greatly developed and extended. This book provides the first comprehensive and authoritative account of the theory of graphical models and is written by a leading expert in the field. It contains the fundamental graphtheory required and a thorough study of Markov properties associated with various type of graphs. The statistical theory of log-linear and graphical models for contingency tables, covariance selection models, and graphical models with mixed discrete-continous variables in developed detail. Specialtopics, such as the application of graphical models to probabilistic expert systems, are described briefly, and appendices give details of the multivarate normal distribution and of the theory of regular exponential families. The author has recently been awarded the RSS Guy Medal in Silver 1996 forhis innovative contributions to statistical theory and practice, and especially for his work on graphical models.

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The idea of modelling systems using graph theory has its origin in several scientific areas: in statistical physics (the study of large particle systems), in genetics (studying inheritable properties of natural species), and in interactions in contingency tables. The use of graphical models instatistics has increased considerably over ...

Steffen L. Lauritzen is at University of Aalborg.

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Format:HardcoverDimensions:308 pages, 9.13 × 6.14 × 0.83 inPublished:April 30, 1999Publisher:Oxford University Press

The following ISBNs are associated with this title:

ISBN - 10:0198522193

ISBN - 13:9780198522195

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Table of Contents

Introduction1. Graphs and Hypergraphs2. Conditional Independence and Markov Properties3. Contingency Tables4. Multivariate Normal Models5. Models for Mixed Data6. Further topicsA Various PrerequisitesB Linear Algebra and Random VectorsC The Multivariate DistributionD Exponential Models

Editorial Reviews

`...this is an excellent reference book for those who are interested in studying the mathematical theory for graphical models.'Short Book Reviews, vol. 18, no. 1, April 1998