OpenTURNS
BestModelAIC¶
- BestModelAIC(*args)¶
Select the best model according to the Akaike information criterion.
- Parameters
- sample2-d sequence of float
Tested sample.
- modelslist of
DistributionorDistributionFactory Tested distributions.
- Returns
- best_model
Distribution The best distribution for the sample according to Bayesian information criterion. This may raise a warning if the best model does not perform well.
- best_aicfloat
The Akaike information criterion with the best model.
- best_model
See also
FittingTest.AIC
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_aic = ot.FittingTest.BestModelAIC(sample, tested_distributions) >>> print(best_model) Normal(mu = -0.0944924, sigma = 0.989808)