Nothing
"KMest"<-function(xin, cens, xout)
#this is the actual KM estimate not the version that estimates the censoring distribution
{
ordxin <- sort(xin) #order input data=Xi
ordcens <- cens[order(xin)] #order censoring =Di
n <- length(xin)
nn <- length(xout)
vKuse <- sapply(1:nn, function (i, ordxin, xout)
{
k.use<-c(max(which(ordxin <= xout[i])), min(which(xout[i] <= ordxin)))
k.use.1<-ifelse(is.infinite(k.use[2]), c(k.use[1],k.use[1]) , k.use) #cat("k.use = ", k.use, "\n")
l.use<- max(k.use.1)
l.use
}, ordxin, xout)
vK <- vKuse -1
Huse<-sapply(vK, function (i,n,ordcens) {
i<-ifelse(i==-Inf, 0,i)
index<-1:i
expon.use<-ordcens[index]
((n-index+1)/(n-index+2))^expon.use
}
, n, ordcens)
result<-sapply(Huse, prod)
result
}
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