An introduction to generalized linear models / Annette J. Dobson, Adrian G Barnett.
By: Dobson, Annette J
Contributor(s): Barnett, Adrian G
Material type: 

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519.5 DEP 2004 Probability and statistics for engineering and the sciences / | 519.5 DIS 2011 Statistics and scientific method : | 519.5 DOI 2008 An introduction to generalized linear models / | 519.5 DOI 2008 An introduction to generalized linear models / | 519.5 FRS 1994 Statistics : | 519.5 HAS 2013 Statistics with Stata : | 519.5 HOF 2009 A first course in Bayesian statistical methods / |
Includes bibliographical references (p. [295]-301) and index.
Table of contents Model fitting --
Exponential family and generalized linear models --
Estimation --
Inference --
Normal linear models --
Binary variables and logistic regression --
Nominal and ordinal logistic regression --
Poisson regression and log-linear models --
Survival analysis --
Clustered and longitudinal data --
Bayesian analysis --
Markov chain Monte Carlo methods --
Example Bayesian analyses.
Summary:
Offers a cohesive framework for statistical modeling. Emphasizing numerical and graphical methods, this work enables readers to understand the unifying structure that underpins GLMs. It discusses common concepts and principles of advanced GLMs, including nominal and ordinal regression, survival analysis, and longitudinal analysis.
Applied Statistics
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