What about them? You can have priors for regression coefficients of factor variables, which are continuous as @jsocolar explains here: How to do empirical Bayes on factor variables? - #3 by jsocolar. But you can’t have negative binomial prior because that is not continuous. Formulas like ´y ~ age + gender` are ambiguous because they do not show the parameters but whatever model you have in brms, all parameters are going to be continuous. If you really want to have a prior for discrete/categorical unknowns and perform inference on them then it is not going to be as straightforward as just fitting a bmrs model: 7 Latent Discrete Parameters | Stan User’s Guide
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