survSL.rfsrc: Wrapper function for Random Survival Forests prediction...

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

Wrapper function for Random Survival Forests prediction algorithm

Description

This prediciton algorithm uses the rfsrc function from the randomForestSRC package to estimate a survival random forest.

Usage

survSL.rfsrc(time, event, X, newX, new.times, obsWeights, id, ...)

Arguments

time	Observed follow-up time; i.e. minimum of the event and censoring times.
event	Observed event indicator; i.e, whether the follow-up time corresponds to an event or censoring.
X	Training covariate data.frame.
newX	Test covariate data.frame to use for prediction. Should have the same variable names and structure as X.
new.times	Times at which to obtain to obtain the predicted survivals.
obsWeights	Observation weights.
id	Currently ignored
...	Additional arguments passed on to rfsrc.

Value

pred	Matrix of predictions, with the same number of rows as newX and number of columns equal to the length of new.times. Rows index new observations, and columns index new times at which the survival was computed.
fit	One-element list including object, the fitted rfsrc. object.

References

Ishwaran, H., Kogalur, U. B., Blackstone, E. H., & Lauer, M. S. (2008). Random survival forests. The Annals of Applied Statistics, 2(3), 841-860.

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