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Changing s-parameter in PAFit #4
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Hi, |
Hi, |
The strengths of the PA effect and the fit-get-richer effect can be compared between different datasets. In your example, one can compare the estimated attachment exponents and say that the PA effect in the second dataset is stronger than the PA effect in the first dataset. For comparing the fit-get-richer effect, one way is to compare the variances of the estimated fitness distributions. A larger variance implies a stronger fit-get-richer effect. |
Hi,
I've been getting very high s-values when running the PAFit model on my data. How can I decide the value, especially when wanting to compare results for different datasets?
I've tried changing the parameters within the PAfit function but it doesn't work.
Thanks
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