r2dtable {stats}R Documentation

Random 2-way Tables with Given Marginals


Generate random 2-way tables with given marginals using Patefield's algorithm.


r2dtable(n, r, c)



a non-negative numeric giving the number of tables to be drawn.


a non-negative vector of length at least 2 giving the row totals, to be coerced to integer. Must sum to the same as c.


a non-negative vector of length at least 2 giving the column totals, to be coerced to integer.


A list of length n containing the generated tables as its components.


Patefield, W. M. (1981). Algorithm AS 159: An efficient method of generating r x c tables with given row and column totals. Applied Statistics, 30, 91–97. doi:10.2307/2346669.


## 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 ...

[Package stats version 4.4.0 Index]