Nothing
##
## Bartels' Rank Test
##
bartels.rank.test <- function(x, alternative="two.sided", pvalue="normal"){
# Performs Bartels Ratio Test for Randomness.
#
# Args:
# x: a numeric vector containing the data.
# alternative hypothesis, must be one of "two.sided" (default), "left.sided" or "right.sided"
# pv.method: asymptotic aproximation method used to compute the p-value.
#
# Returns:
# statistic: the value of the RVN statistic test and the theoretical mean value and variance of the RVN statistic test.
# n: the sample size, after the remotion of consecutive duplicate values.
# p.value: the asymptotic p-value.
# method: a character string indicating the test performed.
# data.name: a character string giving the name of the data.
# alternative: a character string describing the alternative.
#
dname <- deparse(substitute(x))
# Remove NAs
x<-na.omit(x)
stopifnot(is.numeric(x))
n <- length(x)
if (alternative == "t"){alternative <- "two.sided"}
if (alternative == "l"){alternative <- "left.sided"}
if (alternative == "r"){alternative <- "right.sided"}
if (alternative != "two.sided" & alternative != "left.sided" & alternative != "right.sided")
{stop("must give a valid alternative")}
if (n < 3){stop("sample size must be greater than 2")}
# unique
rk <- rank(x)
d <- diff(rk)
#d.rank <- n*(n^2-1)/12
nm <- sum(rk^2)
d.rank <- nm-n*(mean(rk)^2)
RVN <- sum(d^2)/d.rank
mu <- 2
vr <- (4*(n-2)*(5*n^2-2*n-9))/(5*n*(n+1)*(n-1)^2)
#
# Computes the p-value
if (pvalue == "auto"){
pvalue <- ifelse(n<=100,"beta","normal")
if (n<10) pvalue <- "exact"
}
if (pvalue == "exact"){
pv <- pbartelsrank(q=c(nm-1,nm), n)
pv0 <- pv[2]
pv1 <- pv[1]
}
if (pvalue == "beta"){
btp <- (5*n*(n+1)*(n-1)^2)/(2*(n-2)*(5*n^2-2*n-9))-1/2
pv0 <- pbeta(RVN/4,shape1=btp,shape2=btp)
pv1 <- 1-pv0
}
if (pvalue=="normal") pv0 <- pnorm((RVN - mu) / sqrt(vr))
if (pvalue=="beta" | pvalue=="normal") pv1 <- 1-pv0
#
if (alternative=="two.sided"){
pv <- 2*min(pv0, pv1)
alternative<-"nonrandomness"
}
if (alternative=="left.sided"){
pv <- pv0
alternative<-"trend"
}
if (alternative=="right.sided"){
pv <- pv1
alternative<-"systematic oscillation"
}
test <- (RVN - mu) / sqrt(vr)
rval <- list(statistic = c(statistic=test), nm=sum(d^2), rvn=RVN, mu=mu, var=vr, p.value = pv,
method = "Bartels Ratio Test", data.name = dname, parameter=c(n=n), n=n, alternative=alternative)
class(rval) <- "htest"
return(rval)
}
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