crossfit_surv_preds: Generate cross-fitted conditional survival predictions

In cwolock/survML: Tools for Flexible Survival Analysis Using Machine Learning

Generate cross-fitted conditional survival predictions

Description

Generate cross-fitted conditional survival predictions

Usage

crossfit_surv_preds(time, event, X, newtimes, folds, pred_generator, ...)

Arguments

time	n x 1 numeric vector of observed follow-up times. If there is censoring, these are the minimum of the event and censoring times.
event	n x 1 numeric vector of status indicators of whether an event was observed.
X	n x p data.frame of observed covariate values
newtimes	Numeric vector of times on which to estimate the conditional survival functions
folds	n x 1 numeric vector of folds identifiers for cross-fitting
pred_generator	Function to be used to estimate conditional survival function.
...	Additional arguments to be passed to pred_generator.

Value

Named list of cross-fitted conditional survival predictions

cwolock/survML documentation built on April 17, 2025, 5:17 p.m.