I'm running into a confidence interval on a fit of some data. This is the code I'm using:
x0 = [1 1 1];
fitfun = fittype( @(a,b,c,x) a*x.^b+c)
[fitted_curve,gof] = fit(x,y,fitfun,'StartPoint',x0,'Weight', w, 'Lower', [0,-3,0],'Upper',[1000,0,1])
coeffvals = coeffvalues(fitted_curve);
p = predint(fitted_curve,x,0.001,'Observation','off');
Where w is calculated from inverse cube weighting:
The fit works well for this very small confidence interval (.1 % for .001). When I try to make a more meaningful fit and use 95% confidence, I get this:
Is there a way I can get a closer result for this 95% interval? predint must use "Observation" and "off" (changing to "functional" makes interval smaller, but it's not what I'm looking for).
Thanks so much for your help.