SAS PROC Glimmix permits both R-side and G-side random effects to be specified where the R-side, often the within individual error /residual that arises from either Repeated measures( or a time based multiple) measures, can be specified as an AR(1). The G-side represents the standard covariance matrix (of random intercept and/or random slope) at the group-ID level.

I can specify these models in “nlme” for example using:

rside_gside <- lme(sales ~ tv80+digital30+search50, random = ~1|storeid, correlation=corAR1(form=~1|storeid), data=storesales)

How do I specify both the R-side and G-side in brms?

Looks like many of the popular options are covered. Instead of AR(1), is it possible to specify a fully parameterized / unstructured R matrix for correlated observations within independent stores?