An Introduction to Generalized Linear Models, 3rd

Annette J. Dobson, Adrian Barnett

ISBN 10: 1439889198 / ISBN 13: 9781439889190

Editore: Chapman and Hall, 2011

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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.

Codice articolo K582A0001175

Dati bibliografici

• Titolo: An Introduction to Generalized Linear Models, 3rd
• Editore: Chapman and Hall
• Data di pubblicazione: 2011
• Lingua: Inglese
• ISBN 10: 1439889198
• ISBN 13: 9781439889190
• Rilegatura: Trade paperback
• Edizione: 3rd. INTERNATIONAL EDITION
• Condizione: New in new dust jacket.

Descrizione articolo

Riassunto

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.