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Convert an error function to a least squares fitting?

I have written an error function to compare simulated values to experimental data, but I also want to have a least squares fitting. I know that Mathematica has a function for it, I'm just not sure how that function can compare to what I want. The error function that I have take a difference between simulation and data, then normalizes the difference to the average of the simulation and data at that condition to give a numerical description. Could someone help me in writing a least squares version of this? Example equation pasted below. `errr = 1/

8 ((2 Abs[rcias - rciax])/(rcias + rciax) + (
2 Abs[risus - risux])/(risus + risux) + (2 Abs[rvps - rvpx])/(
rvps + rvpx) + (2 Abs[rmps - rmpx])/(rmps + rmpx) + (
2 Abs[rc - rcx])/(rc + rcx) + (2 Abs[rfm - rfmx])/(
rfm + rfmx) + (2 Abs[rf3 - rf3x])/(rf3 + rf3x) + (
2 Abs[rf2 - rf2x])/(rf2 + rf2x));`
POSTED BY: Josh Wofford
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