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Bayesian Applications

In: Computational Probability

Author

Listed:
  • John H. Drew

    (The College of William and Mary)

  • Diane L. Evans

    (Rose-Hulman Institute of Technology)

  • Andrew G. Glen

    (Colorado College)

  • Lawrence M. Leemis

    (The College of William and Mary)

Abstract

This chapter considers Bayesian applications of APPL. Section 14.1 introduces Bayesian statistics and motivates the use of a computer algebra system to derive posterior distributions. Section 14.2 develops algorithms in the case of a single unknown parameter. Section 14.3 develops algorithms in the case of multiple unknown parameters.

Suggested Citation

  • John H. Drew & Diane L. Evans & Andrew G. Glen & Lawrence M. Leemis, 2017. "Bayesian Applications," International Series in Operations Research & Management Science, in: Computational Probability, edition 2, chapter 14, pages 277-300, Springer.
    • Handle: RePEc:spr:isochp:978-3-319-43323-3_14
    DOI: 10.1007/978-3-319-43323-3_14
    as

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