Basic Bayesian Theory
Recall that for Bayesian inference:
The denominator is the marginal probability of the data, averaged over all possible parameter values weighted by their prior distribution. Formally,
where is the parameter space for .
In the original Metropolis algorithm, given a current -value, and a new -value, the new value is accepted with probability:
Read more about this topic: Bayesian Inference In Phylogeny
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