survFit.ELMmboost: SurvELM SurvFit.ELMmboost

In whcsu/SurvELM: Survival Anlalysis with Extreme Learning Machines

Description

An Extreme Learning Machine Cox Model with Gradient Based Boosting

Usage

## S3 method for class 'ELMmboost'
survFit(object, newdata = NULL, ...)

Arguments

object	An ELMmboost object.
newdata	An optional data frame in which to look for variables with which to predict the survivor function.
...	Additional arguments for mboost.

Value

Object of class survFit with elements

surv	Estimated survival probabilities at the given time points
time	The evaluated given time points.
n.event	Number of observed events at given at time points.

See Also

survFit

Examples

set.seed(123)
require(SurvELM)
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)
elmsurvmodel=ELMmboost(x=trset[,-rii],y=Surv(trset[,rii[1]], trset[,rii[2]]))
sfit=survFit(elmsurvmodel)
# plot the survival probability
plot(sfit, xlab = "Time", ylab = "Survival Probability")

whcsu/SurvELM documentation built on Jan. 28, 2020, 3:07 p.m.