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Tag: scipy.stats

Fit data with a lognormal function via Maximum Likelihood estimators

Could someone help me in fitting the data collapse_fractions with a lognormal function, which has median and standard deviation derived via the maximum likelihood method? I tried scipy.stats.lognormal.fit(data), but I did not obtain the data I retrieved with Excel. The excel file can be downloaded: https://stacks.stanford.edu/file/druid:sw589ts9300/p_collapse_from_msa.xlsx Also, any reference is really welcomed. Answer I couldn’t figure out how to get

Why doesn’t Johnson-SU distribution give positive skewness in scipy.stats?

The code below maps the statistical moments (mean, variance, skewness, excess kurtosis) generated by corresponding parameters (a, b, loc, scale) of the Johnson-SU distribution (johnsonsu). For the range of loop values specified in my code below, no parameter configuration results in positive skewness, only negative skewness, even though it should be possible to parameterize the Johnson-SU distribution to be positively-skewed.

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