  Variational Bayes (VB) has shown itself to be a powerful approximation method
in many application areas. This paper describes some diagnostics methods which
can assess how well the VB approximates the true posterior, particularly with
regards to its covariance structure. The methods proposed also allow us to
generate simple corrections when the approximation error is large. It looks at
joint, marginal and conditional aspects of the approximate posterior and shows
how to apply these techniques in both simulated and real data examples.
