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I have an interpolating function 

pfun[t]

and a data set in the form of

{{t,f}}

what can I do to get a numeric estimate on how closely the function fits the data ?

I read up on how LinearModelFit/NonlinearModelFit has options to display r-squared value, but this doesn't suit my case as I already have a function and don't need to fit anything.

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something like so, sum of squares of error:

 (pfun[#[[1]]]-#[[2]])^2&/@data //Total
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  • $\begingroup$ decided to calculate as sum of abs values of error divided by number of elements, thank you $\endgroup$
    – Yevhen Melnyk
    Dec 13, 2017 at 3:52

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