Tukey
The Studentized Range Distribution
Functions of the distribution of the studentized range, $R/s$,
where $R$ is the range of a standard normal sample and
$df*s^2$ is independently distributed as
chi-squared with $df$ degrees of freedom, see pchisq
.
- Keywords
- distribution
Usage
ptukey(q, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE)
qtukey(p, nmeans, df, nranges = 1, lower.tail = TRUE, log.p = FALSE)
Arguments
- q
- vector of quantiles.
- p
- vector of probabilities.
- nmeans
- sample size for range (same for each group).
- df
- degrees of freedom for $s$ (see below).
- nranges
- number of groups whose maximum range is considered.
- log.p
- logical; if TRUE, probabilities p are given as log(p).
- lower.tail
- logical; if TRUE (default), probabilities are $P[X \le x]$, otherwise, $P[X > x]$.
Details
If $ng =$nranges
is greater than one, $R$ is
the maximum of $ng$ groups of nmeans
observations each.
Value
ptukey
gives the distribution function and qtukey
its
inverse, the quantile function.The length of the result is the maximum of the lengths of the
numerical arguments. The other numerical arguments are recycled
to that length. Only the first elements of the logical arguments
are used.
Note
A Legendre 16-point formula is used for the integral of ptukey
.
The computations are relatively expensive, especially for
qtukey
which uses a simple secant method for finding the
inverse of ptukey
.
qtukey
will be accurate to the 4th decimal place.
Source
qtukey
is in part adapted from Odeh and Evans (1974).
References
Copenhaver, Margaret Diponzio and Holland, Burt S. (1988) Multiple comparisons of simple effects in the two-way analysis of variance with fixed effects. Journal of Statistical Computation and Simulation, 30, 1--15.
Odeh, R. E. and Evans, J. O. (1974) Algorithm AS 70: Percentage Points of the Normal Distribution. Applied Statistics 23, 96--97.
See Also
Distributions for standard distributions, including
pnorm
and qnorm
for the corresponding
functions for the normal distribution.
Examples
library(stats)
if(interactive())
curve(ptukey(x, nm = 6, df = 5), from = -1, to = 8, n = 101)
(ptt <- ptukey(0:10, 2, df = 5))
(qtt <- qtukey(.95, 2, df = 2:11))
## The precision may be not much more than about 8 digits:
summary(abs(.95 - ptukey(qtt, 2, df = 2:11)))