brms: development version 2.9.0
R version 3.6.0
RStudio version 1.1.442
Rtools version 3.5
Rstan version 2.19.1
StanHeaders version 2.18.1-9
This is a maximally simple mock dataset, designed to exemplify how varying-intercept logistic models work:
require(brms) set.seed(2019) d <- data.frame(id = letters[1:20], TrueLogit = rnorm(20), y = NA, n = round(runif(20, min = 5, max = 20))) d$y <- round(plogis(d$TrueLogit) * d$n) mix.b <- brm(y|trials(n) ~ (1|id), family = binomial("logit"), prior = prior(uniform(0,10), class = sd), data = d, iter = 11000) Compiling the C++ model
Then, as soon as the model has compiled and sampling is due to begin, the R session crashes with the following pop-up error window:
R Session Aborted
R encountered a fatal error.
The session was terminated.
[Start New Session]
Interestingly, more complex models do tend to fit without crashing. The author of brms suggested that this might be a Stan problem rather than a brms one.