msSurv_fct

data

fold

fs.method

number of clusters for parallel computing

number of folds in outer cross validation loop (for estimation of the predictive accuracy)

cv.out

number of folds in inner cross validation loop (for model selection on the training set)

cv.in

Number of variables up to which stepwise selection should be carried out. Has to be smaller than n number of observations.

nr.var

as defined in package <code>survAUC</code> time; a positive number restricting the upper limit of the time range under consideration.

c.time


This wrapper function passes the ranking method to further functions.


internal

Estimation of the prediction accuracy in a unified survival AUC
approach. Model selection and prediction estimation based on a survival AUC.
Stepwise model selection, based on several ranking approaches.

msSurv_fct: Function selects for the ranking function approaches

Description

Usage

Arguments