Nothing
ci.lnorm.zou <-
function (meanlog, sdlog, n, ci.type, alpha)
{
theta.2.hat <- sdlog^2/2
pivot <- meanlog + theta.2.hat
limits.mean <- ci.normal.approx(theta.hat = meanlog, sd.theta.hat = sdlog/sqrt(n),
n = n, df = n - 1, ci.type = ci.type, alpha = alpha,
test.statistic = "z")$limits
limits.theta.2 <- ci.norm.var(sdhat = sdlog, n = n, ci.type = ci.type,
alpha = alpha)$limits/2
switch(ci.type, `two-sided` = {
lcl <- exp(pivot - sqrt((meanlog - limits.mean["LCL"])^2 +
(theta.2.hat - limits.theta.2["LCL"])^2))
ucl <- exp(pivot + sqrt((limits.mean["UCL"] - meanlog)^2 +
(limits.theta.2["UCL"] - theta.2.hat)^2))
}, lower = {
lcl <- exp(pivot - sqrt((meanlog - limits.mean["LCL"])^2 +
(theta.2.hat - limits.theta.2["LCL"])^2))
ucl <- Inf
}, upper = {
lcl <- -Inf
ucl <- exp(pivot + sqrt((limits.mean["UCL"] - meanlog)^2 +
(limits.theta.2["UCL"] - theta.2.hat)^2))
})
ci.limits <- c(lcl, ucl)
names(ci.limits) <- c("LCL", "UCL")
ret.obj <- list(name = "Confidence", parameter = "mean",
limits = ci.limits, type = ci.type, method = "Zou", conf.level = 1 -
alpha, sample.size = n, dof = n - 1)
oldClass(ret.obj) <- "intervalEstimate"
ret.obj
}
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