dwilcox(q, m, n, log = FALSE) pwilcox(q, m ,n) qwilcox(p, m, n) rwilcox(nn, m, n, bigdata=F)
bdVector of quantiles. Missing values (
NAs) are allowed.
q represents the sum of the ranks of the sample
x
in
c(x,y) where
y represents the elements of another sample.
bdVector of probabilities. Its values must be between 0 and 1.
Missing values(
NAs) are allowed.
length(nn) is greater than 1, then
length(nn)
random numbers are returned.
x. This must be a positive integer not
greater than 50.
y. Also a positive integer not
greater than 50.
TRUE, an object of type
bdVector is returned.
Otherwise, a
vector object is returned. This argument can be used only if the bigdata library section has been loaded.
TRUE, dwilcox will return the log of the
density, not the density itself.
dwilcox returns values for the exact probability at discrete values of
q.
Other functions return cumulative probability (
pwilcox),
quantiles (
qwilcox), or a random sample (
rwilcox) for the rank sum
probability distribution.
rwilcox causes creation of the dataset
.Random.seed if it does
not already exist, otherwise its value is updated.
Missing values (
NAs) and
+-Infs
are allowed as components of
q,
p, or
nn.
If
q,
m, or
n are vectors or
bdVectors
of different lengths,
m, and
n will be made to conform to the length of
q
by replicating their values cyclically. The values of both
m and
n
are rounded to the nearest integer value before any calculations are made.
If data consist of two random samples, a sample
x of size
m,
and a sample
y (independent of sample
x) of size
n, then
the Wilcoxon rank sum statistic is the sum of the ranks of
x
in the combined sample
c(x,y).
This statistic can then be used for a non-parametric test of
location shift between the parent populations.
The Wilcoxon rank sum statistic takes on values between
m*(m+1)/2 and
m*(m+2*n+1)/2.
For details on the uniform random number generator implemented in S-PLUS,
see the
set.seed help file.
For
wilcox.test, S-PLUS uses the Wilcoxon rank sum test
W (see the BACKGROUND section above), while R computes the Mann and Whitney
U statistic:
For samples
x and
y, for each value of
x, count the number of values of
y that are less than
x. The sum of these counts is
U.
The
W and
U statistics differ by a function of the sample sizes, and thus the Wilcoxon distribution is defined differently between R and S-PLUS.
Hollander, M. and Wolfe, D. (1973). Non-parametric Statistical Methods. Wiley, New York.
pwilcox(24, 4, 6) # the probability of q<=24 dwilcox(11:20,9,3) # probabilities for q <- 11:20