Fast methods to identify linear combinations of predictors while fitting an orsf model.
Arguments
- method
(character) a character string specifying the method for tie handling. If there are no ties, all the methods are equivalent. Valid options are 'breslow' and 'efron'. The Efron approximation is the default because it is more accurate when dealing with tied event times and has similar computational efficiency compared to the Breslow method.
- do_scale
(logical) if
TRUE, values of predictors will be scaled prior to each instance of Newton Raphson scoring, using summary values from the data in the current node of the decision tree.- ...
Further arguments passed to or from other methods (not currently used).
Value
an object of class 'orsf_control', which should be used as
an input for the control argument of orsf.
Details
code from the survival package was modified to make this routine.
Adjust do_scale at your own risk. Setting do_scale = FALSE will
reduce computation time but will also make the orsf model dependent
on the scale of your data, which is why the default value is TRUE.
See also
linear combination control functions
orsf_control(),
orsf_control_cph(),
orsf_control_custom(),
orsf_control_net()