Bayesian Applications

John H. Drew, Diane L. Evans, Andrew G. Glen and Lawrence M. Leemis
Additional contact information
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

Chapter 14 in Computational Probability, 2017, pp 277-300 from Springer

Abstract: 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.

Keywords: Posterior Distribution; Markov Chain Monte Carlo; Likelihood Function; Prior Distribution; Marginal Distribution (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:spr:isochp:978-3-319-43323-3_14

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DOI: 10.1007/978-3-319-43323-3_14

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