I was wondering if there is a way to estimate parameters of Johnson SU distributions parameters with some univariate data.
1 Answers
The parameters can be estimated either from the quantiles or from the moments of the distribution. Moments should only be used if the moments are known exactly as a very large sample is needed to give an accurate estimate of higher moments. Both of these methods are relatively complicated algorithms but the references below should be enough to solve your problems.
The paper below details the method for fitting by quantiles:
https://www.jstor.org/stable/2335153?seq=1#metadata_info_tab_contents
This paper details the method for fitting by moments:
https://www.jstor.org/tc/accept?origin=%2Fstable%2Fpdf%2F2346692.pdf
It's also implemented as part of an open-source R package (written in c):
https://cran.r-project.org/web/packages/SuppDists/index.html
And an open-source Matlab package (written in Matlab):
https://uk.mathworks.com/matlabcentral/fileexchange/46123-johnson-curve-toolbox
eJohnsonSUfromExtDistpackage also fits Johnson's $S_U$ distribution in R. Another possible option may be the functiongamlssfrom the packagegamlss, though I am not sure if it can be made to work for fitting a distribution instead of a more complicated model; another function to look into from the same package isJSU. – Richard Hardy Aug 24 '21 at 10:01