title: Goodness of fit tests in SciPy
body: <p>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 <code>distribution.fit(data)</code> return sane results. What I've been unable to do is create the goodness of fit statistics which I'm used to with the <code>fitdistrplus</code> package in R. Is there a common method for comparing "best fit" from a number of different distributions with SciPy? </p>
  
  <p>I'm looking for something like the Kolmogorov-Smirnov test or Cramer-von Mises or
  Anderson-darling tests</p>