% File src/library/stats/man/Tukey.Rd % Part of the R package, http://www.R-project.org % Copyright 1995-2007 R Core Development Team % Distributed under GPL 2 or later \name{Tukey} \alias{Tukey} \title{The Studentized Range Distribution} \description{ Functions of the distribution of the studentized range, \eqn{R/s}, where \eqn{R} is the range of a standard normal sample and \eqn{df \times s^2}{df*s^2} is independently distributed as chi-squared with \eqn{df} degrees of freedom, see \code{\link{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) } \alias{ptukey} \alias{qtukey} \arguments{ \item{q}{vector of quantiles.} \item{p}{vector of probabilities.} \item{nmeans}{sample size for range (same for each group).} \item{df}{degrees of freedom for \eqn{s} (see below).} \item{nranges}{number of \emph{groups} whose \bold{maximum} range is considered.} \item{log.p}{logical; if TRUE, probabilities p are given as log(p).} \item{lower.tail}{logical; if TRUE (default), probabilities are \eqn{P[X \le x]}{P[X <= x]}, otherwise, \eqn{P[X > x]}{P[X > x]}.} } \details{ If \eqn{n_g =}{ng =}\code{nranges} is greater than one, \eqn{R} is the \emph{maximum} of \eqn{n_g}{ng} groups of \code{nmeans} observations each. } \value{ \code{ptukey} gives the distribution function and \code{qtukey} its inverse, the quantile function. } \note{ A Legendre 16-point formula is used for the integral of \code{ptukey}. The computations are relatively expensive, especially for \code{qtukey} which uses a simple secant method for finding the inverse of \code{ptukey}. \code{qtukey} will be accurate to the 4th decimal place. } \references{ Copenhaver, Margaret Diponzio and Holland, Burt S. (1988) Multiple comparisons of simple effects in the two-way analysis of variance with fixed effects. \emph{Journal of Statistical Computation and Simulation}, \bold{30}, 1--15. } \seealso{ \code{\link{pnorm}} and \code{\link{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))) } \keyword{distribution}