hsbadr / bayesian

Bindings for Bayesian TidyModels

Home Page:https://hsbadr.github.io/bayesian/

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Interested in collaboration to identify next set of feaures?

JamesHWade opened this issue · comments

Hi @hsbadr. I like what you have hear so far!

It looks like there some missing features in this package, and I'd love to help you build out this package even more. I see you have testing identified as a good first issue. I can help with that!

I have just begun a project to translate Solomon Kurz's companion book to Statistical Rethinking that uses brms.

Interested in collaborating?

Here's the model I'm currently working on (the first one in the book):

 brm(
    w | trials(36) ~ 0 + Intercept, 
    data = list(w = 24),
    family = binomial(link = "identity"),
    prior =  prior(beta(1, 1), class = b, lb = 0, ub = 1),
    seed = 2,
    file = "fits/b02.01"
  )

Here's as close as I got:

dat <- tibble(w = 24, n = 36)
b2.1_rec <- 
   recipe(w ~ 0, 
          data = dat) |> 
  step_intercept()

b2.1_mod <- 
   bayesian(family = binomial(),
            # formula.override =  brms::brmsformula(w | trials(n) ~ 0),
            prior = prior(beta(1, 1), class = b, lb = 0, ub = 1),
            seed = 2) |> 
   set_engine("brms")

b2.1_workflow <- 
  workflow() |> 
  add_recipe(b2.1_rec) |> 
  add_model(b2.1_mod) |> 
  fit(data = dat)