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Negative binomial regression

Author: Joseph M Hilbe
Publisher: Cambridge, UK ; New York : Cambridge University Press, 2011.
Edition/Format:   eBook : Document : English : Second editionView all editions and formats
Summary:
"This second edition of Hilbe's Negative Binomial Regression is a substantial enhancement to the popular first edition. The only text devoted entirely to the negative binomial model and its many variations, nearly every model discussed in the literature is addressed. The theoretical and distributional background of each model is discussed, together with examples of their construction, application, interpretation,  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Hilbe, Joseph.
Negative binomial regression.
Cambridge ; New York : Cambridge University Press, 2011
(DLC) 2010051121
(OCoLC)694679188
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Joseph M Hilbe
ISBN: 9781139012010 1139012010 9781139011228 1139011227 9781139011488 1139011480 9780511973420 051197342X
OCLC Number: 712560113
Description: 1 online resource (xviii, 553 pages) : illustrations
Contents: The concept of risk --
Overview of count response models --
Methods of estimation --
Assessment of count models --
Poisson regression --
Overdispersion --
Negative binomial regression --
Negative binomial regression: modeling --
Alternative variance parameterizations --
Problems with zero counts --
Censored and truncated count models --
Handling endogeneity and latent class models --
Count panel models --
Bayesian negative binomial models --
Appendix A. Constructing and interpreting interactions terms --
Appendix B. Data sets, commands, functions.
Responsibility: Joseph M. Hilbe.
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Abstract:

A substantial enhancement of the only text devoted entirely to the negative binomial model and its many variations.  Read more...

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'Students, developers, and practitioners in this area will all want to have this thorough guide close at hand. The wealth of theory and extensive applications using 'real' data sets and contemporary Read more...

 
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