In Andrew Gelman’s paper, he states
“Estimating the marginal likelihood is more challenging, because determining the normalization constants Z\k requires multivariate integrations”
I have a couple of question. If you already found the full posterior from EP, then there should be no more concern about the normalization constant. Unless, the EP exercise only derived the posterior to within a constant?
Even if you do have a normalization constant, at the end each marginal distribution (for a single variable) has to integration to 1, so that should solve that problem. What’s wrong with this view?