The Chi-Squared goodness of fit test.
procedure GOFChi2Test(const Data: TVec; Distribution: TDistribution; NumBins: Integer; out hRes: THypothesisResult; out Signif: double; hType: THypothesisType = htTwoTailed; Alpha: double = 0.05); overload;
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Parameters |
Description |
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Data |
Samples to be tested. |
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Distribution |
Distribution name (string). At the moment the following string values are supported : 'beta', 'exponential', 'gamma', 'normal', 'rayleigh' and 'weibull'. |
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NumBins |
Number of frequency histogram bins. |
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hRes |
Returns the result of the null hypothesis (default assumption is that data comes from specific distribution). |
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Signif |
(Significance level) returns the probability of observing the given result by chance given that the null hypothesis is true. |
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hType |
Defines the type of the null hypothesis (left, right and two - tailed). |
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Alpha |
Defines the desired significance level. If the significance probability (Signif) is bellow the desired significance (Alpha), the null hypothesis is rejected. |
Performs the Chi-squared goodness of fit test to test if data is coming from specific distribution. This overload version does not require expected and actual frequencies, but only data vector.
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