sorry if this is a stupid question, but how do I specify a half-normal (or folded) prior in brms in order to test a directional hypothesis of a categorical variable on normally distributed data (in my case, effect of unexpected/expected stimulus on EEG data), with a regular linear mixed model? using ub or lb does not seem to give the right prior since it gives lower density near zero than a half-normal would, if I understand correctly, but that’s as close as I seem to get to anything directional.

priors <- c(set_prior(“normal(0,1)”, class = “Intercept”),

set_prior(“normal(0,.5)”, class = “b”, coef = “” , lb = 0))

Please also provide the following information in addition to your question:

- Operating System: mac osx
- brms Version: 2.4.0