eclipse modeling

Schiminovich and I met briefly today with his undergraduate researcher Adam Greenberg (Columbia), who is going to look at doing a better job of fitting the eclipses we have discovered in the GALEX time-domain data. His first order of business is to implement a solid-disk-on-solid-disk eclipse model; then look at better models. We discussed how to parameterize and initialize the model so that simple local optimization should work.

Throughout the day, Phil Marshall, Douglas Applegate (Stanford), and I had a long and detailed discussion about Bayesian evidence (or Bayes factors) as compared to cross-validation in model selection. This is an issue that I have been thinking about a lot and these two helped me sharpen up and modify my thinking substantially. Despite being a Bayesian in practice, I don't believe that most uses of the Bayesian evidence in the literature are correct or justified, mainly because the integral depends so much on aspects of the prior which are (in practice) chosen by the investigator not via an introspective or probabilistic analysis of her or his true prior beliefs but rather more-or-less at random. That is, the prior doesn't really represent prior belief. In this, I am closer to Andrew Gelman (Columbia), who sees the prior as a pragmatic (and testable) regularization of the problem; indeed Gelman and I discussed this point in a separate thread this week.