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First I have to say that I am not that code-savvy. With that out of the way, I have these data sets that look Gaussian, but they're not. With some literature review, other people have found that they fit a super-Poissonian distribution. So, I have been trying to code in Matlab and OriginLab an equation to describe a super-Poissonian distribution. I have found that the are two ways, but the easiest one seems to be to multiply a factor of alpha to the distribution and the resulting random variable. You can see a very quick and nice description here: https://math.stackexchange.com/questions/1245024/is-there-a-analytical-formula-for-super-and-sub-poissonian-distributions

The result from all this is that none of the programs are able to fit, it says the fit doesn't converge. Any help will be greatly appreciated.

eaz
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    Please clarify your question. Is a fit (which function?) not converging or are you incapable of implementing a super-Poisson distribution? In both cases have a look on how to provide a [MVE](https://stackoverflow.com/help/minimal-reproducible-example). We help with code, it's not a coding service ;) – max Mar 30 '20 at 15:14
  • Hello, I'm not asking for the code. I'm asking for insight. And if you look under the provided link it literally says that the fits are not converging. The OriginLab software is not fitting anything I throw at it. I'm just wondering if anyone ran into this issue or have an idea on how to solve it. That's all, but thanks anyway. – eaz Mar 31 '20 at 13:16

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