Generalized Linear Models (2nd Edn) (Monographs on Statistics and Applied Probability) (Volume 37)

Nelder, John A.

ISBN 10: 0412317605 / ISBN 13: 9780412317606

Published by Chapman & Hall, 1999

About this Item

Volume 37. This is an ex-library book and may have the usual library/used-book markings inside.This book has hardback covers. In fair condition, suitable as a study copy. No dust jacket. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,900grams, ISBN:9780412317606.

Seller Inventory # 4345283

Bibliographic Details

• Title: Generalized Linear Models (2nd Edn) (Monographs on Statistics and Applied Probability) (Volume 37)
• Publisher: Chapman & Hall
• Publication Date: 1999
• Language: English
• ISBN 10: 0412317605
• ISBN 13: 9780412317606
• Binding: Hardcover
• Edition: 2nd Edition
• Condition: Fair
• Weight: 900 grams
• Seller catalogs:
  • Mathematics

About this title

Synopsis

The success of the first edition of Generalized Linear Models led to the updated Second Edition, which continues to provide a definitive unified, treatment of methods for the analysis of diverse types of data. Today, it remains popular for its clarity, richness of content and direct relevance to agricultural, biological, health, engineering, and other applications.

The authors focus on examining the way a response variable depends on a combination of explanatory variables, treatment, and classification variables. They give particular emphasis to the important case where the dependence occurs through some unknown, linear combination of the explanatory variables.

The Second Edition includes topics added to the core of the first edition, including conditional and marginal likelihood methods, estimating equations, and models for dispersion effects and components of dispersion. The discussion of other topics-log-linear and related models, log odds-ratio regression models, multinomial response models, inverse linear and related models, quasi-likelihood functions, and model checking-was expanded and incorporates significant revisions.

Comprehension of the material requires simply a knowledge of matrix theory and the basic ideas of probability theory, but for the most part, the book is self-contained. Therefore, with its worked examples, plentiful exercises, and topics of direct use to researchers in many disciplines, Generalized Linear Models serves as ideal text, self-study guide, and reference.

About the Author

P. McCullagh