public class FisherExactDistribution extends EmpiricalDistribution
For small, sparse, or unbalanced data, the exact and asymptotic p-values can be quite different and may lead to opposite conclusions concerning the hypothesis of interest. In contrast the Fisher exact test is, as its name states, exact, and it can therefore be used regardless of the nextSample characteristics.
It becomes difficult to calculate with large samples or well-balanced tables, but fortunately these are exactly the conditions where the chi-square distribution is appropriate.
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FisherExactDistribution(int[] rowSums,
int[] colSums,
int nSim)
Construct the distribution for the Fisher's exact test.
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FisherExactDistribution(int[] rowSums,
int[] colSums,
int nSim,
RandomLongGenerator rng)
Construct the distribution for the Fisher's exact test.
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public FisherExactDistribution(int[] rowSums,
int[] colSums,
int nSim,
RandomLongGenerator rng)
rowSums - row totalscolSums - column totalsnSim - number of simulationsrng - a uniform random number generatorpublic FisherExactDistribution(int[] rowSums,
int[] colSums,
int nSim)
rowSums - row totalscolSums - column totalsnSim - number of simulations