Nothing
eqgevd <-
function (x, p = 0.5, method = "mle", pwme.method = "unbiased",
tsoe.method = "med", plot.pos.cons = c(a = 0.35, b = 0),
digits = 0)
{
if (!is.vector(p, mode = "numeric") || is.factor(p))
stop("'p' must be a numeric vector.")
if (any(!is.finite(p)))
stop("NA/NaN/Inf values not allowed in 'p'.")
if (any(p < 0) || any(p > 1))
stop("All values of 'p' must be between 0 and 1.")
method <- match.arg(method, c("mle", "pwme", "tsoe"))
pwme.method <- match.arg(pwme.method, c("unbiased", "plotting.position"))
tsoe.method <- match.arg(tsoe.method, c("med", "lms", "lts"))
if (x.is.est.obj <- data.class(x) == "estimate" || data.class(x) ==
"estimateCensored") {
if (x$distribution != "Generalized Extreme Value")
stop(paste("'eqgevd' estimates quantiles", "for a generalized extreme value distribution. You have supplied an object",
"that assumes a different distribution."))
class.x <- oldClass(x)
if (!is.null(x$interval)) {
x <- x[-match("interval", names(x))]
oldClass(x) <- class.x
}
location <- x$parameters["location"]
scale <- x$parameters["scale"]
shape <- x$parameters["shape"]
n <- x$sample.size
ret.list <- x
}
else {
if (!is.vector(x, mode = "numeric") || is.factor(x))
stop(paste("'x' must be either a list that inherits from",
"the class 'estimate', or else 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))
ret.list <- egevd(x, method = method, pwme.method = pwme.method,
tsoe.method = tsoe.method, plot.pos.cons = plot.pos.cons)
ret.list$data.name <- data.name
ret.list$bad.obs <- bad.obs
location <- ret.list$parameters["location"]
scale <- ret.list$parameters["scale"]
shape <- ret.list$parameters["shape"]
}
q <- qgevd(p, location = location, scale = scale, shape = shape)
if (length(p) == 1 && p == 0.5)
names(q) <- "Median"
else {
pct <- round(100 * p, digits)
names(q) <- paste(pct, number.suffix(pct), " %ile", sep = "")
}
ret.list <- c(ret.list, list(quantiles = q))
ret.list$quantile.method <- paste("Quantile(s) Based on\n",
space(33), ret.list$method, " Estimators", sep = "")
if (x.is.est.obj)
oldClass(ret.list) <- class.x
else oldClass(ret.list) <- "estimate"
ret.list
}
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