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Negative Binomial Regression

Negative Binomial Regression (Hardback)

£45.00
Unavailable. Replaced by new product or edition.
Unavailable

Synopsis

At last - a book devoted to the negative binomial model and its many variations. Every model currently offered in commercial statistical software packages is discussed in detail - how each is derived, how each resolves a distributional problem, and numerous examples of their application. Many have never before been thoroughly examined in a text on count response models: the canonical negative binomial; the NB-P model, where the negative binomial exponent is itself parameterized; and negative binomial mixed models. As the models address violations of the distributional assumptions of the basic Poisson model, identifying and handling overdispersion is a unifying theme. For practising researchers and statisticians who need to update their knowledge of Poisson and negative binomial models, the book provides a comprehensive overview of estimating methods and algorithms used to model counts, as well as specific guidelines on modeling strategy and how each model can be analyzed to access goodness-of-fit.

Science & MathematicsMathematicsProbability & statistics Publisher: Cambridge University Press Publication Date: 23/08/2007 ISBN-13: 9780521857727  Details: Type: Hardback Format: Books
Availability: Unavailable. Replaced by new product or edition.  

Joseph M. Hilbe is Emeritus Professor of Philosophy, University of Hawaii, and Adjunct Professor of Statistics, Arizona State University; Fellow, American Statistical Association; Fellow, Royal Statistical Society; Software Reviews Editor, The American Statistician (since 1997). His books include Negative Binomial Regression (2007, Cambridge University Press), Generalized Estimating Equations (with J. Hardin; 2002, CRC Press), and Generalized Linear Models and Extensions (with J. Hardin; 2001, 2007, Stata Press).

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