Hi Eric,
You found a bug! The current implementation of StudentFactory is based on a
moment estimator, and the standard deviation is not updated correctly. I
created the associated ticket, it will be fixed soon. In the mean time, you can
use either the MaximumLikelihood or the MethodOfMoments classes. By the way, I
will probably extend the factory to multivariate Student distributions.
Cheers
Régis
Le samedi 7 juillet 2018 à 18:44:35 UTC+2, Eric Marsden
<[email protected]> a écrit :
Hello,
Attempting to fit a Student t distribution to a sample using the
StudentFactory object, I seem to obtain incorrect results:
---
>>> import openturns as ot
>>> sample = ot.Student(4.0, 100.0, 30.0).getSample(1000)
>>> print(ot.StudentFactory().build(sample))
Student(nu = 2.00123, mu = 99.3967, sigma = 1)
---
Using a maximum likelihood approach as per the example in the
documentation works, however.
http://openturns.github.io/openturns/latest/examples/data_analysis/maximumlikelihood_estimator.html
I'm using version 1.10 (from Debian) on Python 3.6.
Thanks,
Eric
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