Variational Bayesian methods: Difference between revisions

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Assume that <math>q(\mu,\tau) = q(\mu)q(\tau)</math>, i.e. that the posterior distribution factorizes into independent factors for <math>\mu</math> and <math>\tau</math>. This type of assumption underlies the variational Bayesian method. The true posterior distribution does not in fact factor this way (in fact, in this simple case, it is known to be a [[Gaussian-gamma distribution]]), and hence the result we obtain will be an approximation.
 
===Derivation of <{{math>|''q''(\''&mu;'')</math>}}===
Then