Nothing
epoisSinglyCensored.half.cen.level <-
function (x, censored, censoring.side, ci, ci.method = "normal.approx",
ci.type, conf.level, ci.sample.size = sum(!censored), pivot.statistic = c("z",
"t"))
{
x[censored] <- x[censored]/2
lambda.hat <- c(lambda = mean(x))
if (ci) {
ci.method <- match.arg(ci.method)
pivot.statistic <- match.arg(pivot.statistic)
ci.obj <- ci.normal.approx(theta.hat = lambda.hat, sd.theta.hat = sqrt(lambda.hat/ci.sample.size),
n = ci.sample.size, df = ci.sample.size - 1, ci.type = ci.type,
alpha = 1 - conf.level, lb = 0, test.statistic = pivot.statistic)
ci.obj$parameter <- "lambda"
return(list(parameters = lambda.hat, ci.obj = ci.obj))
}
else return(list(parameters = lambda.hat))
}
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