cvcb.control {CoxBoost} | R Documentation |
Control paramters for cross-validation in iCoxBoost
Description
This function allows to set the control parameters for cross-validation to be passed into a call to iCoxBoost
.
Usage
cvcb.control(K=10,type=c("verweij","naive"),parallel=FALSE,
upload.x=TRUE,multicore=FALSE,folds=NULL)
Arguments
K |
number of folds to be used for cross-validation. If K is larger or equal to the number of events in the data to be analyzed, leave-one-out cross-validation is performed.
|
type |
way of calculating the partial likelihood contribution of the observation in the hold-out folds: "verweij" uses the more appropriate method described in Verweij and van Houwelingen (1996), "naive" uses the approach where the observations that are not in the hold-out folds are ignored (often found in other R packages).
|
parallel |
logical value indicating whether computations in the cross-validation folds should be performed in parallel on a compute cluster, using package snowfall . Parallelization is performed via the package snowfall and the initialization function of of this package, sfInit , should be called before calling iCoxBoost .
|
multicore |
indicates whether computations in the cross-validation folds should be performed in parallel, using package parallel . If TRUE , package parallel is employed using the default number of cores. A value larger than 1 is taken to be the number of cores that should be employed.
|
upload.x |
logical value indicating whether x should/has to be uploaded to the
compute cluster for parallel computation. Uploading this only once (using sfExport(x) from library snowfall ) can save much time for large data sets.
|
folds |
if not NULL , this has to be a list of length K , each element being a vector of indices of fold elements. Useful for employing the same folds for repeated runs.
|
Value
List with elements corresponding to the call arguments.
Author(s)
Written by Harald Binder binderh@uni-mainz.de.
References
Verweij, P. J. M. and van Houwelingen, H. C. (1993). Cross-validation in survival analysis. Statistics in Medicine, 12(24):2305-2314.
See Also
iCoxBoost
, cv.CoxBoost
[Package
CoxBoost version 1.4
Index]