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Jun 2, 2020 at 18:23 comment added fred85 I think it is really useful in evaluating the number of parameters one might need to effectively fit a certain model. I have fit the model proposed by @MarcoB with n=6 as you suggested and it fits very well. Thanks for mentioning it here.
Jun 2, 2020 at 18:13 comment added JimB AIC simply ranks the models. And then you pick the desired model. AIC does not change the model in any way. So you end up with an analytical expression as desired. But note that some use AIC in a weighting scheme and "average" the models examined (called "model averaging"). I don't recommend that in this case.
Jun 2, 2020 at 16:56 comment added fred85 Thank you. AIC looks interesting and I will definitely read more about it. However, what am looking for is any analytical expression that fits the data. Such expression with be passed to an NIntegrate.
Jun 2, 2020 at 16:43 history undeleted JimB
Jun 2, 2020 at 16:43 history edited JimB CC BY-SA 4.0
Added sermon about choosing a "best" model.
Jun 2, 2020 at 14:46 history deleted JimB via Vote
Jun 2, 2020 at 14:45 history answered JimB CC BY-SA 4.0