Description Usage Arguments Value
A critical difference between this update method and the typical method for other R objects
concerns how centering/scaling of the data is (not) updated. The standardization of variables is
important in survreg_map
, because priors are placed on the standardized scale. So if
updating the data meant re-computing this standardization, the updated vs. original models would
effectively have different priors. Instead, for this update method, whether the standardization
is recomputed is controlled by the 'reeval_scaling_and_terms' argument. If only data are being
updated, this defaults to FALSE, meaning that standardization will *not* be recomputed. This
includes both scaling accomplished by code within survreg_map
(controlled by the
standardize_x
argument), as well as scaling accomplished by transformations in the
formula, such as stats::scale
, stats::poly
, splines::ns
, and other functions
with makepredictcall
methods (this is controlled by the predvars
argument).
1 2 3 |
object |
Object of class |
formula. |
Passed to |
anc. |
A named list of formulas, each of which are passed to |
reeval_scaling_and_terms |
Should scaling and terms be re-computed with new data? For details on scaling see 'Description'. This also controls whether the 'contrasts' and 'xlevels' arguments are updated. Broadly, the idea is to be cross-validation friendly: for example, if new factor-levels are present in a validation-fold that weren't in the training fold, that's OK because all levels of the factor were remembered from the original model-object. |
... |
Slots to update. |
evaluate |
If true evaluate the new call else return the call. |
If evaluate = TRUE the fitted object, otherwise the updated call.
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