How to pass multiple columns of weights to brms - r

Question

I would appreciate any help to specify my brms model below in order to be able to pass multiple columns of weights to the model as illustrated in the stan code below.
I need to do this in brms or stanarm rather than stan directly because I want to use functions of https://github.com/mjskay/tidybayes that are currently not supported by a stanfit object.
#sample data:
dt = read.table(header = TRUE, text = "
n r r/n group treat c2 c1 weights
62 3 0.048387097 1 0 0.1438 1.941115288 1.941115288
96 1 0.010416667 1 0 0.237 1.186583128 1.186583128
17 0 0 0 0 0.2774 1.159882668 3.159882668
41 2 0.048780488 1 0 0.2774 1.159882668 3.159882668
212 170 0.801886792 0 0 0.2093 1.133397521 1.133397521
143 21 0.146853147 1 1 0.1206 1.128993008 1.128993008
143 0 0 1 1 0.1707 1.128993008 2.128993008
143 33 0.230769231 0 1 0.0699 1.128993008 1.128993008
73 62 1.260273973 0 1 0.1351 1.121927228 1.121927228
73 17 0.232876712 0 1 0.1206 1.121927228 1.121927228")
N <- nrow(dt)
n <- dt$n
r <- dt$r
p <- dt$r/n
group <- dt$group
treat <- dt$treat
c1 <- dt$c1
c2 <- dt$c2
w_1 <- dt$weights
w_2 <- dt$weights - 0.01
w_3 <- dt$weights + 0.01/2
w_4 <- dt$weights - 0.01/3
w_5 <- dt$weights + 0.01/4
w_6 <- dt$weights - 0.01/5
w_7 <- dt$weights + 0.01/6
w_8 <- dt$weights + 0.01/7
w_9 <- dt$weights + 0.01/8
w_10 <- dt$weights + 0.01/9
list_bind <- list (N = N,
n = n, r = r, p = p, group = group, treat = treat, c1 = c1, c2 = c2,
weights = cbind(w_1, w_2, w_3, w_4, w_5, w_6, w_7, w_8, w_9, w_10)
)
dt_bind <- as.data.frame(list_bind)
#my attempt:
m <-brm(r | trials(n) + weights(weights.w_1:weights.w_10) ~ treat*c2+(1|group),
data=dt_bind, family=binomial(link=logit))
#stan code:
//this is what I want the brms model specification to be able to do
data {
...
real<lower=0> weights[N, 10]; // data block of model weights
}
model {
...
// likelihood
for (n in 1:N)
for (w in 1:10) {
target += weights[n, w] * binomial_logit_lpmf(Y[n] | trials[n], mu[n]);
}
}
Thanks in advance for any help.