I spent my research time today reading Bretthorst's book on Bayesian spectrum analysis [one big PDF file]. It is a beautiful and useful document; I think there will be many ideas in this book useful to the exoplanet problem. Roweis pointed me to this book; Yavin made me read it.
One small comment on this excellent book, which I am compelled by God and Man to make: Bretthorst, like Jaynes, is a believer in assuming that errors are Gaussian because that is the most conservative thing you can do if you have a noise variance estimate and nothing else. This is technically correct, and beautiful to see demonstrated. However, this is a very dangerous argument, because it only applies when you somehow, magically, know your noise variance. You never do, at best you know the curvature at the mode of the noise distribution (if you are lucky). The variance is dominated in most real systems by rare outliers. No finite experiment is likely to provide you a good estimate of it. Furthermore, even if you do know the variance, how would you know that you know? You would have to take fourth moments to confirm it, and I have never seen an experiment ever in the history of science in which fourth moments are accurately measured. Finally, the conservativeness-of-Gaussian argument is a maximum-entropy argument subject to a strict variance constraint. Jaynes and Bretthorst should know better: You never have absolutely perfect knowledge of anything; the noise should be found through an inferential process, not a constrained exact math problem!
Whew! I had to get that off my chest.