Bayesian Methods

David J. Olive
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David J. Olive: Southern Illinois University, Department of Mathematics

Chapter Chapter 11 in Statistical Theory and Inference, 2014, pp 359-371 from Springer

Abstract: Abstract Two large classes of parametric inference are frequentist and Bayesian methods. Frequentist methods assume that θ $$\boldsymbol{\theta }$$ are constant parameters “generated by nature,” while Bayesian methods assume that the parameters θ $$\boldsymbol{\theta }$$ are random variables. Chapters 1 – 10 consider frequentist methods with an emphasis on exponential families, but Bayesian methods also tie in nicely with exponential family theory.

Keywords: Bayesian Methods; Exponential Family Theory; Squared Error Loss; Bayesian Point Estimator; Conjugate Priors (search for similar items in EconPapers)
Date: 2014
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DOI: 10.1007/978-3-319-04972-4_11

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