Generalized Linear Models (Monographs on Statistics and Applied Probability)

McCullagh, P. and John A. Nelder

ISBN 10: 0412238500 / ISBN 13: 9780412238505

Published by Chapman & Hall, 1983

About this Item

261pp. Very good condition with text clean and binding sound without dust jacket.

Seller Inventory # 222386

Bibliographic Details

• Title: Generalized Linear Models (Monographs on Statistics and Applied Probability)
• Publisher: Chapman & Hall
• Publication Date: 1983
• Language: English
• ISBN 10: 0412238500
• ISBN 13: 9780412238505
• Binding: Hardcover
• 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.