Computational Methods for Bayesian Model Choice (2)

I have updated the slides for the series of four (advanced graduate) lectures about computational methods for Bayesian model choice, they are here:

and I will keep updating them till next Thursday when the course finishes. When giving my lecture this morning, I realised one thing about bridge sampling, namely that, while the principle of estimating the Bayes factor by

applies as soon as both parameter spaces are the same, the estimator is potentially disastrous unless the parameterisations of both models are compatible. I mean, ifin model 1 does not correspond to the same intrinsic quantity asin model 2 (for instance the first moments of x), there is no reason for both posteriors to overlap…

In case you happen to be in Edinburgh tomorrow (with nothing better to do), I am also giving a seminar along those same slides at the James Clark Maxwell Building (LT C) of the Kings Buildings Campus of the University of Edinburgh at 4pm.