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Sets out an integrated approach to statistical inference using the likelihood function as the primary measure of evidence for statistical... Læs mere
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Filling a gap in current Bayesian theory, "Statistical Inference: An Integrated Bayesian/Likelihood Approach" presents a unified Bayesian treatment of parameter inference and model comparisons that can be used with simple diffuse prior specifications.
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The book is based on the model-based theory, used widely by scientists in many fields. It covers simple experimental and survey designs, and probability models up to and including generalised linear (regression) models and some extensions of these, including finite mixtures.