[This article was first published on Xi'an's Og » R, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I just updated my short review on Bayesian computational tools I first wrote in April for the Annual Review of Statistics and Its Applications. The coverage is quite restricted, as I took advantage of two phantom papers I had started a while ago, one with Jean-Michel Marin, on hierarchical Bayes methods and on ABC. (As stressed in the first version, the paper handles missing data, not as a topic, but as a fact!) The running example is the Laplace vs. Gauss model choice problem, first considered in our ABC model choice paper. The referee of the paper was asking for a broader perspective, which makes perfect sense (except that I did not have the time to get that broad). And mentioned a potential missing acknowledgement of priority as Olli’s thesis was using a simple (instead of double) exponential vs. Gauss as its running example. Once again, a plain 25 pages introduction to the topic, not aiming at anything new. The exercise made me ponder whether or not I wanted to engage into it in a near future, with a pessimistic outcome!
