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Bayesian Inference Using Gibbs Sampling in Applications and Curricula of Decision Analysis
2014
INFORMS Transactions on Education
A pplications and curricula of decision analysis currently do not include methods to compute Bayes' rule and obtain posteriors for nonconjugate prior distributions. The current convention is to force the decision maker's belief to take the form of a conjugate distribution, leading to a suboptimal decision. Bayesian inference using Gibbs sampling (BUGS) software, which uses Markov chain Monte Carlo methods, numerically obtains posteriors for nonconjugate priors. By using the decision maker's
doi:10.1287/ited.2013.0120
fatcat:bkjdtlvrkrbxtgvdzj3wov3rmm