How do scipy.stats..fit methods work?

Question

How do distribution fitness-tests, ex. scipy.stats.norm.fit work? Investigation of scipy source code led me to rv_continuous.fit method, but it looks like beating the air. What algorithms are used, Pearson's chi-squared test or some other ones?

UPD As I understood optimization algorithm inside fit finds maximum likelihood estimation. But for example for scipy.stats.norm, maximum likelihood is well-known - it is sample mean for normal mean and square root from sample variance - for sigma. Why it isn't calculated direclty?

*"Why it isn't calculated directly?"* In recent versions of scipy, the MLE parameters computed by the `fit()` method are calculated directly for a few of the distributions, including `norm`. — Warren Weckesser, Jun 23 '16 at 19:05

score 2 · Accepted Answer · answered May 27 '13 at 13:01

2

All rv_continuous.fit seems to be doing is act as a wrapper method for various functions, beginning with fmin, in the optimize class, using the downhill simplex algorithm.

answered May 27 '13 at 13:01

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How do scipy.stats..fit methods work?

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