I have a model I’ve fit in brms where the response is a mixture, with the proportion of the population in each group changing via a GAM smooth:
mix <- mixture(gaussian, gaussian) prior <- c( prior(normal(3, 1), Intercept, dpar = mu1), prior(normal(1, 1), Intercept, dpar = mu2) ) fit1 <- brm(bf(response ~ 1, theta1 ~ s(days, k=15)), data = data, family = mix, prior = prior, chains = 2, stanvars = stanvars)
I’d like to make predictions of
theta1 from a new data frame of
days. How do get at this latent variable?
- Operating System: Debian 9
- brms Version: 2.3.1