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

- Operating System:
- brms Version:

I am working on a longitudinal data where I am fitting a multilevel/ Mixed-effect model expressed as follow

y_{it}|\alpha, \beta_i^s, \sigma^2_{\epsilon}, x_{it} \sim N(y_{it}; \alpha x_{it}+ \beta_i^s z_{it}, \sigma^2_{\epsilon})

where \alpha - fixed effect and \beta_i^s is the “random effect” for individual i. Often we assume \beta_i^s to be distributed normally, i.e \beta_i^s \sim N(0, \sigma^2_{\beta^s}).

Here, I want to relax the above assumption (http://liu.diva-portal.org/smash/get/diva2:916319/FULLTEXT01.pdf) by modelling \beta_i^s as an infinite mixture of Gaussian. That is,

\beta_i^s \sim \sum_{k=1}^{\infty} \eta_k N( \beta_i^s;\beta_k, Q_k), \sum_{k=1}^{\infty} \eta_k =1 for some weights \eta_k.

Is it possible to specify such kind of model in brms or rstan?

Thank you