I have fit a model with a smooth term, including random curves for each subject, using a function like this:

`mod1 = brm(y~s(x, k=4) + s(sid, x, k=4, bs='fs', m=1), family=bernoulli)`

It is more complicated in reality, but this is enough to demonstrate my issue. I am interested in drawing from the posterior of this model excluding the smooth component corresponding to the random curves (generated via `s(sid, x, k=4, bs='fs', m=1)`

). That is to say, I am interested in typical performance rather than individual subject performance. With random slopes or interactions, this would be as simple as setting `re_formula = NA`

, but that does not appear to work.

Is there a non-hacky way to instruct `posterior_linpred`

to ignore smooths corresponding to `s(sid, x, k=4, bs='fs', m=1)`

? If not, I may need to drop back into mgcv. I could post an example if needed.

- Operating System: 10.14.6
- brms Version: 2.9.0