FittingTest_ChiSquared

FittingTest_ChiSquared(*args)

Perform a \chi^2 goodness-of-fit test for 1-d discrete distributions.

Refer to Chi-squared goodness of fit test.

Parameters
sample2-d sequence of float

Tested sample.

modelDistribution or DistributionFactory

Tested distribution.

levelfloat, 0 \leq \alpha \leq 1, optional

This is the risk \alpha of committing a Type I error, that is an incorrect rejection of a true null hypothesis.

n_parametersint, 0 \leq k, 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.

Returns
fitted_distDistribution

Estilmated distribution (if model is of type DistributionFactory).

test_resultTestResult

Test result.

Raises
TypeErrorIf the distribution is not discrete or if the sample is

multivariate.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distribution = ot.Poisson()
>>> sample = distribution.getSample(30)
>>> fitted_dist, test_result = ot.FittingTest.ChiSquared(sample, ot.PoissonFactory(), 0.01)
>>> test_result
class=TestResult name=Unnamed type=ChiSquared Poisson binaryQualityMeasure=true p-value threshold=0.01 p-value=0.698061 statistic=0.150497 description=[Poisson(lambda = 1.06667) vs sample Poisson]