An Introduction to Generalized Linear Models, Third Edition by Annette J. Dobson,Adrian Barnett

By Annette J. Dobson,Adrian Barnett

carrying on with to stress numerical and graphical tools, An creation to Generalized Linear types, 3rd Edition offers a cohesive framework for statistical modeling. This new version of a bestseller has been up-to-date with Stata, R, and WinBUGS code in addition to 3 new chapters on Bayesian research.

Like its predecessor, this variation offers the theoretical heritage of generalized linear types (GLMs) prior to concentrating on equipment for studying specific forms of information. It covers common, Poisson, and binomial distributions; linear regression versions; classical estimation and version becoming tools; and frequentist equipment of statistical inference. After forming this starting place, the authors discover a number of linear regression, research of variance (ANOVA), logistic regression, log-linear versions, survival research, multilevel modeling, Bayesian versions, and Markov chain Monte Carlo (MCMC) tools.

Using well known statistical software program courses, this concise and available textual content illustrates useful techniques to estimation, version becoming, and version comparisons. It comprises examples and routines with whole information units for almost the entire versions covered.

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