Titlebook: Bayesian and Frequentist Regression Methods; Jon Wakefield Textbook 2013 Springer Science+Business Media, LLC, part of Springer Nature 201

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Bayesian Inferences in contrast to the frequentist view described in Chap. 2 in which parameters are treated as fixed .. Specifically, with respect to the inferential targets of Sect. 2.1, the fixed but unknown parameters and hypotheses are viewed as random variables under the Bayesian approach. Additionally, the unk

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Linear Modelsl convenience and the relative ease of parameter interpretation. We discuss a number of issues that require consideration in order to perform a successful linear regression analysis. These issues are relevant irrespective of the inferential paradigm adopted and so apply to both frequentist and Bayes

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General Regression Modelsed linear models (GLMs) and, more briefly, nonlinear models. We first give an outline of this chapter. In Sect.9.2 we describe three motivating datasets to which we return throughout the chapter. The GLMs discussed in Sect.6.3 can be extended to incorporate dependences in observations on the same un

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Book 1977wal. He was extremely active in the scientific world of alcoholism as planner and coordinator of three international conferences, as chairman of the section on Biomedical Research of the I.C.A.A., and as a member of a W.H.O. Task Force on Alcoholism. In addition, he was very active in a variety of s

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