Usage
cv.grpsurvOverlap(X, y, group, ..., nfolds = 10, seed, cv.ind, returnY = FALSE, trace = FALSE)
Arguments
X
The design matrix, without an intercept, as in grpregOverlap.
y
The time-to-event outcome matrix for survival analysis, as explained in grpregOverlap.
group
A list of vectors containing group information, as in grpregOverlap.
...
Additional arguments to grpregOverlap.
nfolds
The number of cross-validation folds. Default is 10.
seed
Set the seed of the random number generator to obtain reproducible results.
cv.ind
User specified indices of which fold each observation belongs to. By default the observations are randomly assigned.
returnY
Should the linear predictors from the cross-validation folds be returned? Default is FALSE; if TRUE, this will return a matrix in which the element for row i, column j is the fitted value for observation i from the fold in which observation i was excluded from the fit, at the jth value of lambda. See details in cv.grpsurv trace
If set to TRUE, print out the progress of the cross-validation. Default is FALSE.