Comments (6)
- I think it fits here. It's still generic so that there is no dependency on where the draws come from, and if pit function would support draws objects it would be natural here. Yesterday @paul-buerkner also agreed initially
- Makes sense
- Makes sense
from posterior.
I think that PIT in posterior does make sense. Will we want to use it for other stuff than plotting though? If yes, than posterior is I think good. If we only ever want to use it for bayesplot, then perhaps also bayesplot could be a reasonable target(?)
from posterior.
Just to clarify, are we talking about the methods or the generic (or both)?
from posterior.
- PIT values could be summarised with scalar diagnostic value, but the preferred way is graphics, but we may want to use other plots than what is available in bayesplot (which is what I was doing)
-
- methods, 2. it would be nice if the method function could be called with any posterior draws object type
from posterior.
from posterior.
Sounds good to me too
from posterior.
Related Issues (20)
- should remove_variables be exported? HOT 4
- Dealing with chains of different length HOT 1
- rvar strange behavior HOT 2
- Add a function to extract single draw of multidimensional variable HOT 4
- .args in summarise draws incompatible with summary functions without ellipses HOT 10
- `pareto_khat(..., tail="both")` returns NA if just one tail is constant
- pareto diagnostics return named values, preventing renaming
- validate_weights allows NaN and NA weights
- [FR] Allow as_draws_dt for data.table HOT 9
- New draws_tensor format? HOT 4
- Applying a function to each chain HOT 1
- In summarise draws, a function that returns a character changes all columns to character HOT 4
- export ps_khat_threshold HOT 4
- pareto_khat should always return the same data structure
- `ps_khat_threshold` can return values greater than 0.7 HOT 2
- Errors when `rvar` is made from a data frame HOT 3
- subset_draws duplicates variables if `variables` argument contains `NA` HOT 4
- New CRAN release? HOT 6
- default for `r_eff` in `pareto_smooth()` and `pareto_khat()` differ
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from posterior.