| Wilcoxon {stats} | R Documentation |
Distribution of the Wilcoxon Rank Sum Statistic
Description
Density, distribution function, quantile function and random
generation for the distribution of the Wilcoxon rank sum statistic
obtained from samples with size m and n, respectively.
Usage
dwilcox(x, m, n, log = FALSE)
pwilcox(q, m, n, lower.tail = TRUE, log.p = FALSE)
qwilcox(p, m, n, lower.tail = TRUE, log.p = FALSE)
rwilcox(nn, m, n)
Arguments
x, q |
vector of quantiles. |
p |
vector of probabilities. |
nn |
number of observations. If |
m, n |
numbers of observations in the first and second sample, respectively. Can be vectors of positive integers. |
log, log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are
|
Details
This distribution is obtained as follows. Let x and y
be two random, independent samples of size m and n.
Then the Wilcoxon rank sum statistic is the number of all pairs
(x[i], y[j]) for which y[j] is not greater than
x[i]. This statistic takes values between 0 and
m * n, and its mean and variance are m * n / 2 and
m * n * (m + n + 1) / 12, respectively.
If any of the first three arguments are vectors, the recycling rule is used to do the calculations for all combinations of the three up to the length of the longest vector.
Value
dwilcox gives the density,
pwilcox gives the distribution function,
qwilcox gives the quantile function, and
rwilcox generates random deviates.
Note
S-PLUS uses a different (but equivalent) definition of the Wilcoxon statistic.
Author(s)
Kurt Hornik
See Also
wilcox.test to calculate the statistic from data, find p
values and so on.
dsignrank etc, for the distribution of the
one-sample Wilcoxon signed rank statistic.
Examples
x <- -1:(4*6 + 1)
fx <- dwilcox(x, 4, 6)
Fx <- pwilcox(x, 4, 6)
layout(rbind(1,2),width=1,heights=c(3,2))
plot(x, fx,type='h', col="violet",
main= "Probabilities (density) of Wilcoxon-Statist.(n=6,m=4)")
plot(x, Fx,type="s", col="blue",
main= "Distribution of Wilcoxon-Statist.(n=6,m=4)")
abline(h=0:1, col="gray20",lty=2)
layout(1)# set back
N <- 200
hist(U <- rwilcox(N, m=4,n=6), breaks=0:25 - 1/2, border="red", col="pink",
sub = paste("N =",N))
mtext("N * f(x), f() = true \"density\"", side=3, col="blue")
lines(x, N*fx, type='h', col='blue', lwd=2)
points(x, N*fx, cex=2)
## Better is a Quantile-Quantile Plot
qqplot(U, qw <- qwilcox((1:N - 1/2)/N, m=4,n=6),
main = paste("Q-Q-Plot of empirical and theoretical quantiles",
"Wilcoxon Statistic, (m=4, n=6)",sep="\n"))
n <- as.numeric(names(print(tU <- table(U))))
text(n+.2, n+.5, labels=tU, col="red")