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
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