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% File src/library/stats/man/r2dtable.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2018 R Core Team
% Distributed under GPL 2 or later
\name{r2dtable}
\alias{r2dtable}
\title{Random 2-way Tables with Given Marginals}
\description{
Generate random 2-way tables with given marginals using Patefield's
algorithm.
}
\usage{
r2dtable(n, r, c)
}
\arguments{
\item{n}{a non-negative numeric giving the number of tables to be
drawn.}
\item{r}{a non-negative vector of length at least 2 giving the row
totals, to be coerced to \code{integer}. Must sum to the same as
\code{c}.}
\item{c}{a non-negative vector of length at least 2 giving the column
totals, to be coerced to \code{integer}.}
}
\value{
A list of length \code{n} containing the generated tables as its
components.
}
\references{
Patefield, W. M. (1981).
Algorithm AS 159: An efficient method of generating r x c tables
with given row and column totals.
\emph{Applied Statistics}, \bold{30}, 91--97.
\doi{10.2307/2346669}.
}
\examples{
## Fisher's Tea Drinker data.
TeaTasting <-
matrix(c(3, 1, 1, 3),
nrow = 2,
dimnames = list(Guess = c("Milk", "Tea"),
Truth = c("Milk", "Tea")))
## Simulate permutation test for independence based on the maximum
## Pearson residuals (rather than their sum).
rowTotals <- rowSums(TeaTasting)
colTotals <- colSums(TeaTasting)
nOfCases <- sum(rowTotals)
expected <- outer(rowTotals, colTotals, "*") / nOfCases
maxSqResid <- function(x) max((x - expected) ^ 2 / expected)
simMaxSqResid <-
sapply(r2dtable(1000, rowTotals, colTotals), maxSqResid)
sum(simMaxSqResid >= maxSqResid(TeaTasting)) / 1000
## Fisher's exact test gives p = 0.4857 ...
}
\keyword{distribution}