orsf_control_cph {aorsf}  R Documentation 
Use the coefficients from a proportional hazards model to create linear combinations of predictor variables while fitting an orsf model.
orsf_control_cph(method = "efron", eps = 1e09, iter_max = 20, ...)
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. 
eps 
(double) When using Newton Raphson scoring to identify
linear combinations of inputs, iteration continues in the algorithm
until the relative change in the log partial likelihood is less than

iter_max 
(integer) iteration continues until convergence
(see 
... 
Further arguments passed to or from other methods (not currently used). 
code from the survival package was modified to make this routine.
For more details on the Cox proportional hazards model, see coxph and/or Therneau and Grambsch (2000).
an object of class 'orsf_control'
, which should be used as
an input for the control
argument of orsf.
Therneau T.M., Grambsch P.M. (2000) The Cox Model. In: Modeling Survival Data: Extending the Cox Model. Statistics for Biology and Health. Springer, New York, NY. DOI: 10.1007/9781475732948_3
linear combination control functions
orsf_control_custom()
,
orsf_control_fast()
,
orsf_control_net()
orsf(data = pbc_orsf,
formula = Surv(time, status) ~ .  id,
control = orsf_control_cph())