Bayesian Statistics: Course Outline
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- Prior information.
- Prior distribution.
- Posterior distributions.
- The posterior means.
- Medians (Bayes estimators under loss functions).
- Variances of univariate and bivariate posterior distributions.
- Non-informative priors.
- Methods of elicitation of hyper parameters of informative priors.
- Bayesian Hypotheses Testing: Bayes factor.
- The highest density region.
- Posterior probability of the hypothesis.
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