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CBpiv<-function (x, CI, S=10^4, Bval=mrank(rep(1,15)),Eta=1.0,Beta=1.0, model="w2", seed=1234, ProgRpt=FALSE)
{
if(length(x)==1) {
N = as.integer(x)
if (N < 2) stop("Insufficient data points")
event<-rep(1,N)
mranks<-mrank(event)
}else{
if(length(x)<2) {
stop("Insufficient data points")
}else{
for(i in 1:length(x)) {
if(x[i]!=1&&x[i]!=0) {
stop("Not an event vector")
}
}
mranks<-mrank(x)
}
}
if (CI <= 0|| CI>=1) stop("Invalid Confidence Interval")
S = as.integer(S/10)*10
if (S < 10^3) {
stop("Insufficient samples")
}
if(S>4*10^9) {
stop("Samples beyond MAX_INT")
}
R2=0.0 ## this diables p-value calculations for this specific CB function run
#seed=1234
if (model == "w2" || model == "W2") {
outdf<-.Call("pivotalMCw2p",mranks, c(R2,CI,Eta,Beta), S, seed, Bval, ProgRpt,
PACKAGE = "pivotals")
}
outdf
}
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