complexity.mincv.CoxBoost {peperr}R Documentation

Interface for CoxBoost selection of optimal number of boosting steps via cross-validation

Description

Determines the number of boosting steps for a survival model fitted by CoxBoost via cross-validation, conforming to the calling convention required by argument complexity in peperr call.

Usage

complexity.mincv.CoxBoost(response, x, full.data, ...)

Arguments

response a survival object (Surv(time, status)).
x n*p matrix of covariates.
full.data data frame containing response and covariates of the full data set.
... additional arguments passed to cv.CoxBoost call.

Details

Function is basically a wrapper around cv.CoxBoost of package CoxBoost. A K-fold cross-validation (default K=10) is performed to search the optimal number of boosting steps, per default in the interval (0, maxstepno=100). The number of boosting steps with minimum mean partial log-likelihood is returned. Calling peperr, the default arguments of cv.CoxBoost can be changed by passing a named list containing these as argument args.complexity.

Value

Scalar value giving the optimal number of boosting steps.

See Also

peperr, cv.CoxBoost


[Package peperr version 1.1-2 Index]