# r2dtable

0th

Percentile

##### Random 2-way Tables with Given Marginals

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

Keywords
distribution
##### Usage
r2dtable(n, r, c)
##### Arguments
n

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

r

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.

c

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

##### Value

A list of length 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. Applied Statistics, 30, 91--97. 10.2307/2346669.

• r2dtable
##### Examples
library(stats) # NOT RUN { ## 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 ... # } 
Documentation reproduced from package stats, version 3.6.0, License: Part of R 3.6.0

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