How do scipy.stats.<distribution>.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?

Answer 1

rv_continuous.fit似乎在做的所有事情都是使用下坡单纯形算法在optimize类中以fmin开头的各种函数的包装方法。