Fix performance summary bugs for subsampled PSIS-LOO CV #475
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the original `mu.bs` has no `NA`s.
…s = TRUE`: If `mu.bs` has `NA`s (which is the case for subsampled PSIS-LOO CV if `baseline = "best"`), then `mu` gets modified by line `mu[is.na(mu.bs)] <- NA` and hence `auc.data` needs to be updated as well.
Previously, `NA` was returned as the AUC for the submodels. This was due to `NA`s not being handled correctly in `auc()`.
…pled PSIS-LOO CV and `deltas = FALSE`.
subsampled PSIS-LOO CV (`nloo`) with `deltas = TRUE` and `baseline = "best"`. For `baseline = "ref"`, this is only a refactor improving the safety and readability of `get_stat()`'s handling of `NA`s because for `baseline = "ref"`, we should always have no `NA`s in `lppd.bs` and `mu.bs`, so in that case, `n_notna` did not require an adjustment and also because the math operations connecting `mu` and `mu.bs` (analogously for `lppd` and `lppd.bs`) ensured that only the "inner join" of non-`NA` elements (i.e., the set of observations for which both `mu` and `mu.bs` (analogously for `lppd` and `lppd.bs`) are not `NA`) is used. This addresses question 1 from <stan-dev#94 (comment)>.
Previously, ```r weighted.sd(numeric(), numeric()) weighted.sd(NA, NA) weighted.sd(NA, NA, na.rm = TRUE) weighted.sd(0.42, 42) ``` returned `0`, `NA_real_`, `0`, `NaN`, respectively. Now, they return `NA_real_`, `NA_real_`, `NA_real_`, `NA_real_`, respectively, just like ```r sd(numeric()) sd(NA) sd(NA, na.rm = TRUE) sd(0.42) ``` .
`stat %in% c("acc", "pctcorr", "auc")` and `!is.null(y_wobs_test$y_prop)`:
`n_notna` was not adapted correctly in that case (because `y_wobs_test$wobs`
usually has non-`NA`s at those places where `mu` has `NA`s).
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fweber144
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Nov 14, 2023
from PR stan-dev#475: Since `.tabulate_stats()` gets arguments from `summary.vsel()` and friends via `...` and passes them over to `get_stat()`, omitting argument `wcv` would have made it possible for users to modify it.
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This fixes several bugs (mainly in
get_stat()) that were sometimes causing incorrect predictive performance results (i.e., point estimate, standard error, confidence interval) in case of subsampled PSIS-LOO CV. For details, see the commit messages.