how to assess the determinability of a model optimised using lsqnonlin?

I have used lsqnonlin to find the best-fit parameters of a model. Now I would like to examine how reliable the optimisation was: I would like to assess the 'determinability' of the model using the Hessian curvature matrix.

In short I need 1) the determinant of the Hessian (d-optimality criterion) 2) the condition number of the hessian (the ratio between its smallest and largest eigenvalues) 3) the m-optimality criterion

The problem is lsqnonlin does not return the Hessian (it does return the Jacobian - can I get the Hessian from that?) I could use hessian.m in the derivest toolbox on the file exchange but it seems to only return one point at a time e.g solve when (x,y) = (1,1). If I looped through for every (x,y) point that I have I don't know how to construct the matrix after that.....

I'm no expert on this stuff so please don't crucify me but point me in the right direction instead!

Thanks,

Aisling