Re: PERT fit with curve_fit function

On Tue, Dec 20, 2022 at 3:28 AM Kevin Sheppard <[email protected]>
wrote:

> If you want a fast method, you should consider a method of moments
> estimator.  You could use the mean, variance, and skewness of your data to
> exactly identify the parameters of the model.  These would lead to
> consistent estimates assuming that the model was correctly specified,
> although it will likely differ from maximum likelihood estimates when it is
> not.
>

I think you'll just run into the same problem.

https://en.wikipedia.org/wiki/Beta_distribution#Four_unknown_parameters

Consider data from a normal distribution which will have roughly 0 skewness
and 0 excess kurtosis. The formula for `alpha + beta` will basically divide
by 0 or otherwise create very large `alpha+beta` values, which was the
problem with the MLE fit.

-- 
Robert Kern

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