T<-c(1,1,2,2,2,3,3,3,3,4,4,5,8,8,8)
d<-c(0,0,1,0,0,1,1,1,0,0,0,1,1,0,0)
library(survival)
s<-Surv(T,d)
?survfit
kmpl<-survfit(s~1,conf.type="p")
kmlog<-survfit(s~1,conf.type="log")
kmllog<-survfit(s~1,conf.type="log-log")
plot(c(0,8),c(0,1),type="n")
lines(kmpl,conf.int=F,lwd=2)
lines(kmpl,conf.int="only",col=2)
lines(kmlog,conf.int="only",col=3)
lines(kmllog,conf.int="only",col=4)


napl<-survfit(s~1,conf.type="p",type="fh")
nalog<-survfit(s~1,conf.type="log",type="fh")
nallog<-survfit(s~1,conf.type="log-log",type="fh")
plot(c(0,8),c(0,3),type="n")
lines(napl,conf.int=F,lwd=2,fun="cumhaz")
lines(napl,conf.int="only",col=2,fun="cumhaz")
lines(nalog,conf.int="only",col=3,fun="cumhaz")
lines(nallog,conf.int="only",col=4,fun="cumhaz")

par(mfrow=c(2,3))
plot(kmpl,col=2)
plot(kmlog,col=3)
plot(kmllog,col=4)
plot(napl,col=2,fun="cumhaz")
plot(nalog,col=3,fun="cumhaz")
plot(nallog,col=4,fun="cumhaz")

# The first option causes confidence intervals not to be generated. 
# The second causes the standard intervals curve +- k *se(curve), where k is determined from conf.int. 
# The log option calculates intervals based on the cumulative hazard or log(survival). 
# The last option bases intervals on the log hazard or log(-log(survival)).