David Dunson forwarded me this article for
a book that is coming out on Nonparametric Bayes in Practice. I think David’s work is great but I keep encountering it in separate research articles and never in a single place which explains when to use each sort of model. I’ll have to read the article in detail, but it seems like a good start. I suggested to David that he write a book but he pointed out that nobody reads books. But do people read articles in handbooks? I don’t know. I guess what’s really needed is a convenient software implementation for all of it. In the meantime, this article seems like the place to go.
I read books, and handbooks, and articles, as an applied statistician who has little difficulty with the math. I'd buy a book on nonparametric Bayesian statistics with an application (not to be confused with cookbook) orientation in an instant – Ghosh, although fun to puzzle through, is not perhaps the most useful of all possible books for the applied statistician.
Software implementations are nice, but really with R and WinBugs a reasonably competent programmer can piece together something useful in a day or two that, although that something won't be as efficient as a nice chunk of C that took some poor graduate student a couple of years to write.
I haven't used it, but i've heard very positive things about DPpackage in R as a way to implement nonparametrics.
http://cran.r-project.org/web/packages/DPpackage/…
I read books, and as yet I am merely an undergrad math major (For example, I read Data Analysis Using Regression and Multilevel/Hierarchical Models for the fun of it and because I enjoy this blog).