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Bayesian Methods

In: Statistical Theory and Inference

Author

Listed:
  • David J. Olive

    (Southern Illinois University, Department of Mathematics)

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.

Suggested Citation

  • David J. Olive, 2014. "Bayesian Methods," Springer Books, in: Statistical Theory and Inference, edition 127, chapter 0, pages 359-371, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-04972-4_11
    DOI: 10.1007/978-3-319-04972-4_11
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