BestModelKolmogorov

BestModelKolmogorov(sample, distributionCollection)

Select the best model according to the Kolmogorov goodness-of-fit test.

Parameters:

sample2-d sequence of float

Tested sample.

modelslist of Distribution

Tested distributions.

Returns:

best_modelDistribution

The distribution that fits the sample best according to the test. This may raise a warning if the best model does not perform well.

best_resultTestResult

Best test result.

See also

FittingTest.Kolmogorov

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distribution = ot.Normal()
>>> sample = distribution.getSample(30)
>>> tested_distributions = [ot.Exponential(), ot.Normal()]
>>> best_model, best_result = ot.FittingTest.BestModelKolmogorov(sample, tested_distributions)
>>> print(best_model)
Normal(mu = 0, sigma = 1)