| Class | Description |
|---|---|
| ApproxFastChiSquareDistribution |
chi-square distribution (distribution of sum of squares of n uniform random variables) (Parameter: n; mean: n; variance: 2*n) The chi-square distribution is a special case of the Gamma distribution (shape parameter = n/2.0, scale = 2.0).
|
| ChiSquareDistribution |
chi-square distribution (distribution of sum of squares of n uniform random variables) (Parameter: n; mean: n; variance: 2*n) The chi-square distribution is a special case of the Gamma distribution (shape parameter = n/2.0, scale = 2.0).
|
| ChiSquareTest |
chi-square test
|
| ContigencyTable |
Class for permuting contigency tables and determining the likelihood of the table. If determining of the probability of a 2x2 table use FisherExact as it is much faster.
|
| ExponentialDistribution |
exponential distribution. (Parameter: lambda; mean: 1/lambda; variance: 1/lambda^2) The exponential distribution is a special case of the Gamma distribution (shape parameter = 1.0, scale = 1/lambda).
|
| FisherExact |
This does a Fisher Exact test. The Fisher's Exact test procedure calculates an exact probability value for the relationship between two dichotomous variables, as found in a two by two crosstable. The program calculates the difference between the data observed and the data expected, considering the given marginal and the assumptions of the model of independence. It works in exactly the same way as the Chi-square test for independence; however, the Chi-square gives only an estimate of the true probability value, an estimate which might not be very accurate if the marginal is very uneven or if there is a small value (less than five) in one of the cells. It uses an array of factorials initialized at the beginning to provide speed. There could be better ways to do this.
|
| GammaDistribution |
gamma distribution. (Parameters: shape, scale; mean: scale*shape; variance: scale^2*shape)
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| LikelihoodRatioTest |
Likelihood ratio test based on chi-square statistics
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| NormalDistribution |
normal distribution (pdf, cdf, quantile)
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| ParetoDistribution |
Pareto distribution (scale-free distribution without characteristic length scale). Parameters: shape parameter k>0, scale parameter m>0 ("minimum income")
|
| PenalizedLikelihood |
Penalized likelihood criteria
|