microquasars, cross-validation

I prepped for my first class in our stats for grad students series by making up some notation for leave-one-out cross-validation, for which I am going to advocate in situations where you need to make a decision and you don't have any serious thoughts about your utility. It surprises many that I am against using marginalized likelihood (Bayes evidence). But I am against it because that is what you would compute in order to mix models, not to decide between them! Also, it is strongly dependent on your priors, when anything you want to use for deciding should be strongly dependent on your utility. And it is super-hard to compute in most circumstances. And so on.

David Russell (Canarias) gave a seminar today on the relationships between microquasars and quasars, and what those things might tell us about how jets are powered. He showed some outrageous phenomenology, including beautiful jet–plasma interactions and a fundamental plane of accreting (hard state) black holes.

1 comment:

  1. I'm struck by how closely your class schedule matches up with the topic list of a "Data Analysis for Physicists" course I plan to pitch. Either these topics *need* to be taught, or I've completely bought into the Camp Hogg approach, hook, line & sinker.

    Some questions about the class:
    - Are you directing your course at intro or advanced grad students?
    - Do you plan to address students' tendencies to fall back to intro-physics-lab style statistics & fits? For example, by having them work examples early on that fail miserably with the typical Gaussian assumptions?