Dear All,

I am trying to calculate the 95% confidence interval on parameters for my model fitted 
using lsqcurvefit. The portion of the code and my function are attached below. The 
curvefit is working great overall and the fitted parameters seem correct. But I am having 
trouble calculating the CIs.

First of all, is nlparci the correct function to use for this purpose?
If it is not, can someone please guide me on how to get the CIs for the fitted parameters? 
If it is, then I have a big problem since for two or three of the parameters, the CIs are huge

(in thousands to millions) and I am not sure why. 

I am using Matlab 6.5, R13.

I appreciate your help!
Best,
Suhrud.

[testpars,resnorm,residual,exitflag,output,lambda,jacobian] = lsqcurvefit('myfunction', 
temp_vect, data, ydata, LB, UB, options);
    
cint = nlparci(testpars,residual,jacobian);

The function is:
A* [g*(exp(k*cos(x-μ1)/2*pi*Bessel_function(k))-DC2]*exp(t-μ2)^2 /
2*sigma^2).

(Von mises function multiplied with Gaussian).