Handling missing values in predictor when outcome is a Multivariate Normal distribution

I actually consider this an incomplete solution (not for you, but for PyMC). If you have a partially observed multivariate normal, the correct prior for the unobserved components is the conditional distribution at the observed components. See here for the wiki, or here for discussion and code examples. It would be nice if we could automatically handle this for users.