Example with family "multinomial"

#1

Hi,
Can anyone suggest an example including r-code that uses the family “multinomial” in brms?

I cannot find anywhere how to specify the model.
Thanks

  • Operating System: windows 10
  • brms Version: 2.8.0
#2

Here is an example with dummy data:

N <- 15
dat <- data.frame(
    y1 = rbinom(N, 10, 0.3), y2 = rbinom(N, 10, 0.5), 
    y3 = rbinom(N, 10, 0.7), x = rnorm(N)
)
dat$size <- with(dat, y1 + y2 + y3)
dat$y <- with(dat, cbind(y1, y2, y3))

prior <- prior(normal(0, 10), "b", dpar = muy2) +
    prior(cauchy(0, 1), "Intercept") +
    prior(normal(0, 2), "Intercept", dpar = muy3)
fit <- brm(bf(y | trials(size)  ~ 1, muy2 ~ x), data = dat, 
                family = multinomial(), prior = prior)

You may also bind y1 to y3 together within the formula as long as you avoid using cbind which is (currently still) reseverd form multivariate models.

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#3

Thank you very much for taking the time.

I cannot fully understand the model because I do not get what you did here:

I tried to look up

> dpar

in

set_prior {brms}

But I could not find how to define it and what, muy2/muy3 are.
I understood they are not arbitrary names because changing them I get the following error message:

> xxx is not a valid distributional or non-linear parameter

Could you tell me where to find these info?

Thank you again

#4

The name of the distributional parameters in multinomial models are mu<category name> (whereas the first category will serve as the reference by default). You only need to use those if you want to fit predictor terms of different structure to different categories. If you want to apply the same structure to all categories (except for the reference of course), you can simply write

bf(y | trials(size) ~ <predictor term>)
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