easystats / easystats/performance
support for multivariate models
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- R
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Description
It would be wonderful to have support for multivariate models (or I'm missing a key part).
library(brms)
library(easystats)
mod1 <- brm( mpg ~ cyl, data = mtcars, chains = 1)
mod2 <- brm( bf(mvbind(mpg,hp) ~ cyl) + set_rescor(FALSE), data = mtcars, chains = 1)
check_model(mod1)
check_model(mod2)
check_model(mod2, resp='mpg')
Both of the last two return
Error in minfo$is_linear && !minfo$is_gam : invalid 'x' type in 'x && y'
which is perhaps because insight::model_info returns a list of lists of the expected components?
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reproducing the brms examples in the issue with check_model(mod2) and check_model(mod2, resp='mpg'). Inspect how insight::model_info represents multivariate models and where minfo$is_linear is evaluated. Done means both multivariate calls work without the invalid 'x' type error while the univariate example continues to work.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Quiet
- Clarity
- Mostly clear
- Newbie friendliness
- 48/100