- Operating System: macOS
- brms Version: 2.17.0
Since brms 2.17.0, several of the post-processing functions return draws from an lprior
parameter, which seems new. Here’s a quick example:
library(brms)
fit <- brm(
data = epilepsy,
family = poisson,
count ~ 1
)
posterior_summary(fit)
as_draws_df(fit)
Estimate Est.Error Q2.5 Q97.5
b_Intercept 2.110184 0.022768989 2.065641 2.153492
lprior -1.970318 0.003358909 -1.976841 -1.963891
lp__ -1644.344975 0.741538245 -1646.383320 -1643.840654
# A draws_df: 1000 iterations, 4 chains, and 3 variables
b_Intercept lprior lp__
1 2.1 -2 -1644
2 2.1 -2 -1644
3 2.1 -2 -1644
4 2.1 -2 -1644
5 2.1 -2 -1644
6 2.1 -2 -1644
7 2.1 -2 -1644
8 2.1 -2 -1644
9 2.1 -2 -1644
10 2.1 -2 -1644
# ... with 3990 more draws
# ... hidden reserved variables {'.chain', '.iteration', '.draw'}
I didn’t see any documentation on lprior
in the updated brms reference manual and it wasn’t mentioned in the NEWS file. So my questions are:
- What is the new
lprior
parameter? - What should applied researchers do with
lprior
?