| SignRank {stats} | R Documentation |
Density, distribution function, quantile function and random
generation for the distribution of the Wilcoxon Signed Rank statistic
obtained from a sample with size n.
dsignrank(x, n, log = FALSE) psignrank(q, n, lower.tail = TRUE, log.p = FALSE) qsignrank(p, n, lower.tail = TRUE, log.p = FALSE) rsignrank(nn, n)
x,q |
vector of quantiles. |
p |
vector of probabilities. |
nn |
number of observations. If length(nn) > 1, the length
is taken to be the number required. |
n |
number(s) of observations in the sample(s). A positive integer, or a vector of such integers. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]. |
This distribution is obtained as follows. Let x be a sample of
size n from a continuous distribution symmetric about the
origin. Then the Wilcoxon signed rank statistic is the sum of the
ranks of the absolute values x[i] for which x[i] is
positive. This statistic takes values between 0 and
n(n+1)/2, and its mean and variance are n(n+1)/4 and
n(n+1)(2n+1)/24, respectively.
If either of the first two arguments is a vector, the recycling rule is used to do the calculations for all combinations of the two up to the length of the longer vector.
dsignrank gives the density,
psignrank gives the distribution function,
qsignrank gives the quantile function, and
rsignrank generates random deviates.
Kurt Hornik
wilcox.test to calculate the statistic from data, find p
values and so on.
dwilcox etc, for the distribution of two-sample
Wilcoxon rank sum statistic.
par(mfrow=c(2,2))
for(n in c(4:5,10,40)) {
x <- seq(0, n*(n+1)/2, length=501)
plot(x, dsignrank(x,n=n), type='l', main=paste("dsignrank(x,n=",n,")"))
}