predict.survSuperLearner: Prediction function for survival Super Learner

In tedwestling/survSuperLearner: Super Learning for Conditional Survival Functions with Right-Censored Data

Prediction function for survival Super Learner

Description

This function predicts the fitted survival Super Learner on new data.

Usage

## S3 method for class 'survSuperLearner'
predict(
  object,
  newdata,
  new.times,
  X = NULL,
  time = NULL,
  event = NULL,
  onlySL = FALSE,
  threshold = 1e-04,
  ...
)

Arguments

object	Fitted survSuperLearner object.
newdata	r x p data.frame of new covariates for which to obtain predicted survivals. Must have same names and structure as original covariates X used to train the SuperLearner.
new.times	q x 1 vector of times for which to obtain predicted survivals.
X	Original training covariates, which may be needed for obtaining predictions for some learners. Defaults to NULL.
time	Original training follow-up times, which may be needed for obtaining predictions for some learners. Defaults to NULL.
event	Original training event indicators, which may be needed for obtaining predictions for some learners. Defaults to NULL.
onlySL	Logical indicating whether to only fit the learners with non-zero SuperLearner coefficient. Defaults to FALSE.
threshold	Minimum coefficient weight for a learner to be inclued in the super learner prediction. Helps reduce computation time if there are many learners with small weights. Defaults to 10e-4.

Details

This is the prediction function for survSuperLearner.

Value

survSuperLearner returns a named list with the following elements:

call	The matched call.
event.libraryNames, cens.libraryNames	Parsed learner names.
event.SL.library, cens.SL.library	Libraries used for fitting.
event.SL.predict, cens.SL.predict	m x k matrices of SuperLearner predicted survival values. Rows index observations in newX; columns index times in new.times.
event.coef, cens.coef	Fitted SuperLearner coefficients for the model for the conditional survival functions for the event and censoring times, respectively.

tedwestling/survSuperLearner documentation built on Dec. 12, 2024, 4:16 p.m.