- It reveals the interrelationships between multiple variables and features of the underlying conditional independence. - It covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. - Many numerical examples and exercises with solutions are included. Num Pages: 462 pages, black & white illustrations, black & white tables, figures. BIC Classification: PBT; PBWH. Category: (P) Professional & Vocational. Dimension: 229 x 153 x 26. Weight in Grams: 648. . 2009. 1st Edition. Paperback. . . . .

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Bibliographic Details

Title: Graphical Models in Applied Multivariate Statistics
Publisher: John Wiley & Sons Inc
Publication Date: 2008
Language: English
ISBN 10: 0470743662
ISBN 13: 9780470743669
Binding: Soft cover
Edition: 1st Edition
Condition: New

About this title

Synopsis

The Wiley Paperback Series makes valuable content more accessible to a new generation of statisticians, mathematicians and scientists.

Graphical models--a subset of log-linear models--reveal the interrelationships between multiple variables and features of the underlying conditional independence. This introduction to the use of graphical models in the description and modeling of multivariate systems covers conditional independence, several types of independence graphs, Gaussian models, issues in model selection, regression and decomposition. Many numerical examples and exercises with solutions are included.

This book is aimed at students who require a course on applied multivariate statistics unified by the concept of conditional independence and researchers concerned with applying graphical modelling techniques.

About the Author

Joe Whittaker is the author of Graphical Models in Applied Multivariate Statistics, published by Wiley.

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