ELMSurv (version 0.6)

predict.ELMCoxBAR: Predict.ELMCoxBAR

Description

Predicting with an ELMCoxBAR model

Usage

# S3 method for ELMCoxBAR
predict(object, newdata, ...)

Arguments

object

An object that inherits from class ELMBJEN.

newdata

A data frame in which to look for variables with which to predict.

...

Additional arguments.

Value

produces a vector of predictions or a matrix of predictions

References

• Wang, H, Li, G. Extreme learning machine Cox model for high-dimensional survival analysis. Statistics in Medicine. 2019; 38:2139-2156.

Examples

# NOT RUN {
set.seed(123)
require(ELMSurv)
require(survival)
#Lung DATA
data(lung)
lung=na.omit(lung)
lung[,3]=lung[,3]-1
n=dim(lung)[1]
L=sample(1:n,ceiling(n*0.5))
trset<-lung[L,]
teset<-lung[-L,]
rii=c(2,3)
# Default with lin_kernel 
elmsurvmodel=ELMCoxBAR(x=trset[,-rii],y=Surv(trset[,rii[1]], trset[,rii[2]]))
# with  the RBF kernel
elmsurvmodel=ELMCoxBAR(x=trset[,-rii],y=Surv(trset[,rii[1]], 
trset[,rii[2]]),Kernel_type="RBF_kernel",Kernel_para=c(2,1))
#The predicted linear predictor
testprelin=predict(elmsurvmodel,teset[,-c(rii)])
# }