survcoxlasso_train {survcompare} | R Documentation |
Trains CoxLasso, using cv.glmnet(s="lambda.min")
Description
Trains CoxLasso, using cv.glmnet(s="lambda.min")
Usage
survcoxlasso_train(
df_train,
predict.factors,
inner_cv = 5,
fixed_time = NaN,
retrain_cox = FALSE,
verbose = FALSE
)
Arguments
df_train |
data frame with the data, "time" and "event" should describe survival outcome |
predict.factors |
list of the column names to be used as predictors |
inner_cv |
k in k-fold CV for lambda tuning |
fixed_time |
not used here, for internal use |
retrain_cox |
whether to re-train coxph on non-zero predictors; FALSE by default |
verbose |
TRUE/FALSE prints warnings if no predictors in Lasso |
Value
fitted CoxPH object with coefficient of CoxLasso or re-trained CoxPH with non-zero CoxLasso if retrain_cox = FALSE or TRUE
[Package survcompare version 0.1.2 Index]