Arrays x and y fit the equation y = a/(x-b)+c almost perfectly, but this was the only technique I could come up with to incorporate the x-shift caused by the constant 'b'.
f = @(b)(polyfitNormR((x - b).^-1, y));
xAdjustment = fminsearch(f,0);
function [normr] = polyfitNormR(x,y)
[~,errorData] = polyfit(x,y,1);
normr = errorData.normr;
end
It works perfectly every time, but I have one particular instance where I get a bunch of warnings and it runs extremely slowly. The fits still look good but I would like to avoid a code that causes warnings in some circumstances. The reason it shows a warning is because fminsearch somehow reduces the array 'x' to essentially the same number on the order of 1E-4 or smaller (even though I am originally passing an array on the order of 1E-1).
Warning: Polynomial is badly conditioned. Add points with distinct X values, reduce the degree of the polynomial, or try centering and
scaling as described in HELP POLYFIT.
I am looking for either a different technique to find this best fit, or an explanation of how to amend my code to avoid this warning using the current technique.
