Let me start by saying that I’m very inexperienced in this area, so go easy on me @Tamas_Papp :wink:. I have two datasets that are similar in shape and I’m trying to fit a distribution to each of them with the goal of being able to make probability statements about the processes that generated the d…

Sorry, I have no idea why you pinged me above, except possibly if you want to fit a distribution using Bayesian methods. This would be able to answer all your questions, but requires some prior expertise. For this distribution in particular, a standard recommendation would be trying overdispersed fa…

This data seems to be truncated at 0, you can take natural log of it and then fit the log form data to certain distributions.

If I got you correctly, you just need a fitting distribution and there is no need that the parameters of the distribution have any meaning. So you are actually free to define your own distribution to fit the data. What speaks against a PDF of f = \frac{1}{n} \sum_{i=1}^n \lambda_i exp(-\lambda_i …

Without more information about how these data were generated and your end goals, it’s going to be pretty difficult for anyone to help. That said, you probably want to look into zero-inflated models. One approach is to fit separate processes for the zeros and the positives. Here you’d have something …

How do I fit a distribution to these data sets?!

Specific Domains Statistics

MatFi September 1, 2019, 5:59am 6

I just have lerned from this thread that there is EmpiricalCDFs which should fulfill your purpose as well

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How do I fit a distribution to these data sets?!

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