aylmer (version 1.0-2)

aylmer.test: A Generalization of Fisher's exact test

Description

A generalization of Fisher's exact test; much of the documentation and Rcode is inspired by fisher.test()

Usage

aylmer.test(x, alternative = "two.sided", simulate.p.value = FALSE,
n = 1e5, B = 2000, burnin = 100, use.brob = FALSE)
aylmer.function(x, func, simulate.p.value = FALSE, n = 1e5, B = 2000,
burnin=100, use.brob=FALSE, DNAME=NULL) 
prob(x, give.log=TRUE, use.brob = FALSE)

Arguments

x

A matrix, possibly with some NA entries, coerced to integer (an object of class board)

alternative

Indicates the alternative hypothesis. If not a function, it must be one of two.sided, greater or less. You may specify just the initial letter. Only used in cases with one degree of freedom

simulate.p.value

Boolean, with default FALSE meaning to return the results of an exact (combinatorial) test, and TRUE meaning to compute p-values by Monte Carlo simulation

n

Integer specifying the maximum number of boards to list if simulate.p.value is FALSE; passed to allprobs() and thence no.of.boards(). This argument has a finite default value to prevent infi

B

Integer specifying the number of replicates used in the Monte Carlo version of the test

burnin

Integer specifying the length of burn in. See details section

use.brob

Boolean, with default FALSE meaning to use IEEE arithmetic and TRUE meaning to use Brobdingnagian arithmetic

give.log

In function prob(), Boolean with default TRUE meaning to return the logarithm of the answer and FALSE meaning to return the value

func

In function aylmer.function(), the test function used. The p-value returned is the probability that a random permissible board has a test function less than that of argument x

DNAME

In function aylmer.function(), the name of the dataset to be specified; default value of NULL means to use standard construction

Value

• An object of class htest

Details

If simulate.p.value is TRUE, a vector of random probabilities is used instead of the full enumeration. A total of B+burnin boards are generated of which the first burnin are discarded.

References

• Ronald Aylmer Fisher 1955.Statistical methods for research workers, Oliver and Boyd
• G. H. Freeman and J. H. Halton 1951.Note on an Exact Treatment of Contingency, Goodness of Fit and Other Problems of Significance. Biometrika, 38(1-2):141-149
• A. W. Ghent 1972.A Method for Exact Testing of 2x2, 2x3, 3x3, and Other Contingency Tables, Employing Binomial Coefficients. American Midland Naturalist, 88(1):15-27
• R. K. S. Hankin 2007.Very Large Numbers in R: Introducing Package Brobdingnag, R news 3(3):15-16
• M. J. Silvapulle and P. K. Sen 2005.Constrained statistical inference. Wiley (page 326 for a special case of the tests performed byaylmer.function())

See Also

fisher.test, randomprobs

Examples

data(iqd)

aylmer.test(iqd)
aylmer.test(iqd)

aylmer.test(iqd,simulate.p.value=TRUE)

data(frogs)
prob(frogs)
prob(frogs,use.brob=TRUE)