Goodness of fit tests in SciPy

Question

I'm new to Python and coming from the R world. I'm trying to fit distributions to sample data using SciPy and having good success. I can make distribution.fit(data) return sane results. What I've been unable to do is create the goodness of fit statistics which I'm used to with the fitdistrplus package in R. Is there a common method for comparing "best fit" from a number of different distributions with SciPy?

I'm looking for something like the Kolmogorov-Smirnov test or Cramer-von Mises or Anderson-darling tests

Answer 1

There's also statmodels goodness of fit tests.

Answer 2

See the scipy.stats library: http://docs.scipy.org/doc/scipy/reference/stats.html

It contains K-S and Anderson-Darling, although apparently not Cramer-von Mises.