Joseph Delaney writes: I [Delaney] am starting to see the hot take of “why don’t we experiment with giving only one dose of an mRNA vaccine”. For example, see this. We briefly brought up one such argument a couple weeks … Continue reading
Probabilistic programming languages I think of BUGS and Stan as probabilistic programming languages because their variables may be used to denote random variables, with function application doing the right thing in terms of propagating randomness (usually encoding uncertainty in a … Continue reading
Fränzi and Tobias‘s book is now real: Fränzi Korner-Nievergelt, Tobias Roth, Stefanie von Felten, Jérôme Guélat, Bettina Almasi, and Pius Korner-Nievergelt (2015) Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan. Academic Press. This is based … Continue reading
Elsewhere: 1. They asked me to write about my “favorite election- or campaign-related movie, novel, or TV show” (Salon) 2. The shopping period is over; the time for buying has begun (NYT) 3. If anybody’s gonna be criticizing my tax … Continue reading
Douglas Anderton informed us that, in a Linux system, you can’t call OpenBugs from R using bugs() from the R2Winbugs package. Instead, you should call Jags using jags() from the R2jags package. P.S. Not the Rotter’s Club guy.
Hey, I don’t think I ever posted a link to this. It’s a discussion in the journal Statistics in Medicine of an article by David Lunn, David Spielhalter, Andrew Thomas ,and Nicky Best. (Sorry but I can’t find the Lunn et al. article online, or I’d link to it.) Anyway, here’s my discussion. Once upon a time . . .
I first saw BUGS in a demonstration version at a conference in 1991, but I didn’t take it seriously until over a decade later, when I found that some of my Ph.D. students in political science were using Bugs to fit their models. It turned out that Bugs’s modeling language was ideal for students who wanted to fit complex models but didn’t have a full grasp of the mathematics of likelihood functions, let alone Bayesian inference and integration. I also learned that the modular structure of BUGS was a great way for students, and researchers in general, to think more about modeling and less about deciding which conventional structure should be fit to data.
Since then, my enthusiasm for BUGS has waxed and waned, depending on what sorts of problems I was working on. For example, in our study of income and voting in U.S. states [1], my colleagues fit all our models in BUGS. Meanwhile we kept running into difficulty when we tried to expand our model in different ways, most notably when going from varying-intercept multilevel regressions, to varying-intercept, varying-slope regressions, to models with more than two varying coefficients per group. Around this time I discovered lmer [2], a function in R which fits multilevel linear and generalized linear models allowing for varying intercepts and slopes. The lmer function can have convergence problems and does not account for uncertainty in the variance parameters, but it is faster than Bugs and in many cases more reliable-so much so that Jennifer Hill and I retooled our book on multilevel models to foreground lmer and de-emphasize Bugs, using the latter more as a way of illustrating models than as a practical tool.
What does BUGS do best and what does it do worst?
ENGREF, 19 avenue du Maine, 75014 Paris (Salle 208) 9h30 – 10h15 : Posterior predictive checking and generalized graphical models (Andrew Gelman, Columbia University – Department of Statistics) 10h15 – 10h35 : Pause 10h35 – 11h20 : Conditional predictive p-values … Continue reading
I programmed a Bugs model (see below) and got this horrible and useless error message: Bugs opened a “Trap: incompatible copy” window, and there was nothing in the log window but this:
display(log)
check(C:\DOCUME~1\ANDREW~1\LOCALS~1\Temp\RtmpMCdEbN/pewpoststrat2.bug.txt)
No syntax error, no nothing. My first thought, of course, was that there was something wrong with the default directory, but when I copied the “schools” example over, it worked fine. So I went through the laborious process of debugging, stripping down the code until I could get it to run and then gradually adding back lines until it crashed. I still couldn’t figure out what was wrong so I brought Matt over and he figured it out at a glance.
Here was the original code: Continue reading
Sandra McBride writes: My current model (in Winbugs) runs very slowly on my very slow laptop, so I am getting a new desktop. Here are some questions in the hopes of speeding up my model: Is Winbugs or Openbugs multithreaded? … Continue reading
I don’t know anything about this but it could be useful, I think. From the Bugs mailing list, David Stivers writes: Continue reading
Peter Park writes, Continue reading
Bob O’Hara has a new blog with stuff on OpenBugs (see here). Feel free to ask him when they’re going to set up the new OpenBugs so it can work with R2WinBUGS!
Jarrett Byrnes writes, A number of us use JAGS, so we import the results of our Bayesian analysis using coda, so I whipped up a quick mcmc2bugs script so that we could also use the functions in R2WinBUGS. I don’t … Continue reading
Jouni wrote a little R program that allows you to write a Bugs model as an R function. His “fitbugs” program then parses the R function and runs Bugs. It’s just a convenience, but it allows you to set up … Continue reading
Our new book on regression and multilevel models is written using R and Bugs. But we’d also like, in an appendix, to quickly show how to fit multilevel models using other software, including Stata, Sas, Spss, MLWin, and HLM (and others?). We’d really appreciate your help in getting sample code for these packages.
We’ve set up five simple examples. I’ll give them below, along with the calls in R that would be used to fit the models. We’re looking for the comparable commands in the other languages. We don’t actually need anyone to fit the models, just to give the code. This should be helpful for students who will be learning from our book using other software platforms. Continue reading
Neal writes, Continue reading
This one’s just for the bugs.R users out there . . . Continue reading
DIC (the Deviance Information Criterion of Spiegelhalter et al.) is a good idea and, I think, the right way to generalize AIC (the Akaike Information Criterion) when trying to get a rough estimate of predictive accuracy for complex models. We … Continue reading
I’m coding up a new adaptive sampler in Python, which is super exciting (the basic methodology is due to Nawaf Bou-Rabee and Tore Kleppe). Luckily for me, another great colleague, Edward Roualdes, has been keeping me on the straight and … Continue reading
This is Jessica. Null results are hard to take. This may seem especially true when you preregistered your analysis, since technically you’re on the hook to own up to your bad expectations or study design! How embarrassing. No wonder some … Continue reading