Comments (2)
I can't remember if pdbart()
has never worked for rbart()
but I think it used to - @vdorie am I imagining this? If not, it would be great functionality to add (and I'm working on fixing some other issues)
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Looks like this was never available functionality, because the partials in my plague WNA paper are all from the models before adding the random intercepts (it's the same model trained with and without RI's, no other differences). I'd just do that in your use case, but in the long run, I should probably add a warning to partial() unless Vince adds this feature!
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Related Issues (20)
- "velox" was removed from CRAN HOT 2
- bart.flex doesn't allow prior adjusting
- Categorical variables not recognized HOT 3
- Dropped variable problem HOT 1
- Spatial covariates HOT 1
- velox dependency HOT 3
- Error in varim.diag "can't find `dropnames`" HOT 2
- cutoff value? HOT 2
- Conflicted "select" function between raster and dplyr. HOT 3
- Requiremed Number of Covariates HOT 1
- R version 4.0.5
- plot.mcmc does not work with masked raster layers HOT 3
- Error from `bart.step()` related to `select()` call HOT 2
- predict() gives completely flat prediction at 0.5 HOT 1
- Saved RI model objects may not retain saved trees HOT 4
- categorical variables mishandled by `varimp`, `variable.step`, `bart.step` HOT 4
- open thread: small vignette HOT 1
- Allow data frame y.data instead of vector
- Conservative partial plot extent
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