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International Edition

Intl. Ed.

An Introduction to Generalized Linear Models, 3rd

Intl. Ed.

An Introduction to Generalized Linear Models, 3rd Papercover - 2008

by Dobson, Annette J, And Barnett, Adrian G

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***INTERNATIONAL EDITION*** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments contain tracking numbers. Great professional textbook selling experience and expedite shipping service.

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Details

  • Title An Introduction to Generalized Linear Models, 3rd
  • Author Dobson, Annette J, And Barnett, Adrian G
  • Binding Paperback
  • Edition 3rd edition
  • Condition New
  • Pages 307
  • Volumes 1
  • Language ENG
  • Publisher Chapman and Hall/CRC
  • Publication date 2008-05
  • Illustrated Yes
  • Bookseller's Inventory # MIG-582
  • ISBN 9781584889502 / 1584889500
  • Weight 0.99 lbs (0.45 kg)
  • Dimensions 9.18 x 6.1 x 0.65 in (23.32 x 15.49 x 1.65 cm)
  • Category Mathematics
  • Library of Congress subjects Linear models (Statistics)
  • Library of Congress Catalogue Number 2008013034
  • Dewey Decimal Code 519.5
  • Quantity available 50

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Reader reviews for An Introduction to Generalized Linear Models, 3rd

From the publisher

Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian analysis.

Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods.

Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons. It includes examples and exercises with complete data sets for nearly all the models covered.

First line

This book is designed to introduce the reader to generalized linear models; these provide a unifying framework for many commonly used statistical techniques.
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