Nothing
zTestGevdShape <-
function (x, pwme.method = "unbiased", plot.pos.cons = c(a = 0.35,
b = 0), alternative = "two.sided")
{
if (!is.vector(x, mode = "numeric") || is.factor(x))
stop("'x' must be a numeric vector")
data.name <- deparse(substitute(x))
if ((bad.obs <- sum(!(x.ok <- is.finite(x)))) > 0) {
is.not.finite.warning(x)
x <- x[x.ok]
warning(paste(bad.obs, "observations with NA/NaN/Inf in 'x' removed."))
}
n <- length(x)
if (n < 3 || length(unique(x)) < 3)
stop(paste("'x' must contain at least 3 non-missing distinct values. ",
"This is not true for 'x' =", data.name))
pwme.method <- match.arg(pwme.method, c("unbiased", "plotting.position"))
alternative <- match.arg(alternative, c("two.sided", "less",
"greater"))
est.list <- egevd(x, method = "pwme", pwme.method = pwme.method,
plot.pos.cons = plot.pos.cons)
shape.hat <- est.list$parameters["shape"]
sd.shape.hat <- sqrt(0.5633/n)
ret.list <- z.test.normal.approx(theta.hat = shape.hat, sd.theta.hat = sd.shape.hat,
hyp.theta = 0, alternative = alternative)
names(ret.list$estimate) <- "shape"
names(ret.list$null.value) <- "shape"
ret.list$method <- "Z-test of shape=0 for GEVD"
ret.list <- c(ret.list, list(estimation.method = est.list$method,
sample.size = n, data.name = data.name, bad.obs = bad.obs))
oldClass(ret.list) <- "htestEnvStats"
ret.list
}
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