Hi,

I’m wondering what is happening behind the scenes when I use brms::update to fit a model to new data. Do posteriors from the original model influence the updated model?

I’ve been searching the web and brms/stan documentation, but I’m coming up short on answers.

Here’s a reproducible example

```
library(brms)
set.seed(1 )
data1 <- data.frame(x = rnorm(1000)) # data for species 1
data1$y = data1$x + rnorm(1000, 0, .01)
data2 <- data.frame(x = rnorm(10)) # data for species 2
data2$y = data2$x + rnorm(10, 0, 2)
plot(y~x, data1, col = "red")
points(y~x, data2, col = "blue")
prior <- prior(normal(0, 5), nlpar = "a") +
prior(normal(0, 5), nlpar = "b")
m1 <- brm( bf( y ~ x * a + b,
a + b ~ 1,
nl = TRUE), data = data1, prior = prior, sample_prior = T)
m2 <- brm( bf( y ~ x * a + b,
a + b ~ 1,
nl = TRUE), data = data2, prior = prior, sample_prior = T)
m3 <- update(m1, newdata = data2)
# is there a difference between how m2 and m3 were fit or are they functionally the same procedure?
```

with gratitude,

joe