Please also provide the following information in addition to your question:
- Operating System: win10
- brms Version: newest
tree <- gl(3,100) d0<-rnorm(300,5,1) t<-5 dt<-d0^(1/3)*rnorm(300,0.5,0.1)*t+d0 mydat<-data.frame(tree,d0,dt) fit_mydat <- brm( bf(dt ~ (beta * (1 - alpha) * 5 + d0^(1-alpha))^(1/(1-alpha)), beta ~ 1, alpha ~ 1, nl = TRUE), data = mydat, family = gaussian(), prior = c( prior(lognormal(0.5, 0.05), nlpar = "beta"), prior(normal(0.3, 0.01), nlpar = "alpha") ), control = list(adapt_delta = 0.95) )
In my case, the nlpar alpha belongs to a normal (0.3, 0.01) distribution, I want to replace the sd (i.e. 0.01) with randomed samples from a different distribution, such as normal (0.01, 0.005). Is it possible to do this in brms?