FittingTest_ChiSquared¶

FittingTest_ChiSquared(*args)

Perform a goodness-of-fit test for 1-d discrete distributions.

Refer to Chi-squared goodness of fit test.

Parameters: sample : 2-d sequence of float Tested sample. model : Tested distribution. level : float, , optional This is the risk of committing a Type I error, that is an incorrect rejection of a true null hypothesis. n_parameters : int, , optional The number of parameters in the distribution that have been estimated from the sample. This parameter must not be provided if a DistributionFactory was provided as the second argument (it will internally be set to the number of parameters estimated by the DistributionFactory). It can be specified if a Distribution was provided as the second argument, but if it is not, it will be set equal to 0. test_result : TestResult Test result. TypeError : If the distribution is not discrete or if the sample is multivariate.

Notes

This is an interface to the chisq.test function from the ‘stats’ R package.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distribution = ot.Poisson()
>>> sample = distribution.getSample(30)
>>> ot.FittingTest.ChiSquared(sample, ot.PoissonFactory(), 0.01)
class=TestResult name=Unnamed type=ChiSquaredPoisson binaryQualityMeasure=true p-value threshold=0.01 p-value=0.606136 description=[]