Nothing
cvmGofTest <-
function (x, distribution = c("norm", "lnorm", "lnormAlt", "zmnorm",
"zmlnorm", "zmlnormAlt"), est.arg.list = NULL)
{
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."))
}
distribution <- match.arg(distribution)
if (any(distribution == c("lnorm", "lnormAlt")) && any(x <=
0))
stop("All values of 'x' must be positive for a lognormal distribution")
if (any(distribution == c("zmlnorm", "zmlnormAlt")) && any(x <
0))
stop(paste("All values of 'x' must be non-negative for a",
"zero-modified lognormal distribution"))
if (length(unique(x)) < 7)
stop(paste("'x' must contain at least 7 distinct non-missing values.",
"This is not true for 'x' =", data.name))
est.fcn <- paste("e", distribution, sep = "")
ret.list <- do.call(est.fcn, c(list(x = x), est.arg.list))
nrl <- names(ret.list)
names(ret.list)[match("parameters", nrl)] <- "distribution.parameters"
names(ret.list)[match("method", nrl)] <- "estimation.method"
ret.list$data.name <- data.name
ret.list$bad.obs <- bad.obs
ret.list$dist.abb <- distribution
new.x <- switch(distribution, norm = x, lnorm = , lnormAlt = log(x),
zmnorm = x[x != 0], zmlnorm = , zmlnormAlt = log(x[x >
0]))
n <- length(new.x)
test.list <- nortest::cvm.test(new.x)
ret.list <- c(ret.list, list(statistic = test.list$statistic,
parameters = n, p.value = test.list$p.value, alternative = paste("True cdf does not equal the\n",
space(33), ret.list$distribution, " Distribution.",
sep = ""), method = "Cramer-von Mises GOF", data = x))
names(ret.list$parameters) <- "n"
ret.list <- ret.list[c("distribution", "dist.abb", "distribution.parameters",
"n.param.est", "estimation.method", "statistic", "sample.size",
"parameters", "p.value", "alternative", "method", "data",
"data.name", "bad.obs")]
oldClass(ret.list) <- "gof"
ret.list
}
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