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The application of graph theory to modelling systems began in several scientific areas, among them statistical physics (the study of large particle systems), genetics (studying inheritable properties of natural species), and interactions in contingency tables. The use of graphical models in statistics has increased considerably in these and other areas such as artificial intelligence, and the theory has been greatly developed and extended. This is the first comprehensive and authoritative account of the theory of graphical models. Written by a leading expert in the field, it contains the fundamentals graph required and a thorough study of Markov properties associated with various type of graphs, the statistical theory of log-linear and graphical models, and graphical tables with mixed discrete-continuous variables in developed detail. Special topics, such as the application of graphical models to probabilistic expert systems, are described briefly, and appendices give details of the multivariate normal distribution and of the theory of regular exponential families.
- Sales Rank: #837445 in Books
- Published on: 1996-07-25
- Original language: English
- Number of items: 1
- Dimensions: 9.50" h x .86" w x 6.38" l, 1.38 pounds
- Binding: Hardcover
- 312 pages
Review
"An excellent research monograph in mathematical statistics. . . .Highly recommended."--Choice
"This research monograph provides a comprehensive account of the theory of graphical models in multivariate statistics written by a leading expert in the field."--Mathematical Review
About the Author
Steffen L. Lauritzen is a Professor in the Department of Mathematics and Computer Science at the University of Aalborg, Denmark and was previously Professor of Statistics at Oxford University.
Most helpful customer reviews
1 of 2 people found the following review helpful.
Great book
By Amazon Customer
This book is hot and popping! But seriously, it is a great read for anyone wanting to learn the theory behind graphical models.
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