Tukey {stats}

R Documentation

The Studentized Range Distribution

Description

Functions of the distribution of the studentized range, R/s, where R is the range of a standard normal sample and df \times s^2 is independently distributed as chi-squared with df degrees of freedom, see pchisq.

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 n_g =nranges is greater than one, R is the maximum of n_g 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). Computation of the distribution of the maximum studentized range statistic with application to multiple significance testing of simple effects. Journal of Statistical Computation and Simulation, 30, 1–15. doi:10.1080/00949658808811082.

Odeh, R. E. and Evans, J. O. (1974). Algorithm AS 70: Percentage Points of the Normal Distribution. Applied Statistics, 23, 96–97. doi:10.2307/2347061.

See Also

Distributions for standard distributions, including pnorm and qnorm for the corresponding functions for the normal distribution.

Examples

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)))

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