Lecture 20 | Bayesian analysis
In Bayesian analysis, before data is observed, the unknown parameter is modeled as a random variable having a probability distribution f ( ), called the prior distribution. This distribution represents our prior belief about the value of this parameter. Conditional on = , the observed data Xis assumed to have distribution f Xj (xj ), where f Xj ...
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