BestModelLilliefors

BestModelLilliefors(sample, factoryCollection)

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

Parameters:
sample2-d sequence of float

Tested sample.

modelslist of DistributionFactory

Tested distribution factories.

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.

Examples

>>> import openturns as ot
>>> ot.RandomGenerator.SetSeed(0)
>>> distribution = ot.Normal()
>>> sample = distribution.getSample(30)
>>> tested_distributions = [ot.ExponentialFactory(), ot.NormalFactory()]
>>> best_model, best_result = ot.FittingTest.BestModelLilliefors(sample, tested_distributions)
>>> print(best_model)
Normal(mu = -0.0944924, sigma = 0.989808)

Examples using the function

Select fitted distributions

Select fitted distributions