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OVERVIEW OF BAYESIAN INFERENCE: PART 1
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THE BAYESIAN APPROACH IN A NUTSHELL
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HOW DOES ONE DO THIS?
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HISTORICAL NOTES
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Example: Infer mean of normal distribution with known variance
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Example: model for allelic count with Beta prior
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Mixtures of conjugate densities
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Joint, Conditional and Marginal Posterior Distributions
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Marginal posterior densities
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Conditional posterior distributions
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BAYESIAN ANALYSIS OF CLASSICAL LINEAR REGRESSION MODEL (normal distribution of residuals, “uninformative” priors)
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2) Model for allelic count with Beta prior
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Binary Data: Predictive distribution
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Example of predictive distribution: beta-binomial model with composition sampling
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Bayes factor for 2 beta-binomial models
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Posterior Predictive Distributions
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