From Spinach Documentation Wiki
Estimate of the Jacobian matrix of a vector valued function of n variables.
[jac,err] = jacobianest(fun,x0)
Simple finite difference estimation.
fun - (vector valued) analytical function to differentiate. fun must be a function of the vector or array x0. x0 - vector location at which to differentiate fun If x0 is an nxm array, then fun is assumed to be a function of n*m variables.
jac - array of first partial derivatives of fun. Assuming that x0 is a vector of length p and fun returns a vector of length n, then jac will be an array of size (n,p) err - vector of error estimates corresponding to each partial derivative in jac.
Version 2.2, authors: John D'Errico