Jacobian Matrix

The first-order derivative of a continuous and differentiable function F (of multiple parameters) is sometimes called the Jacobian matrix J of F (at some specific values of parameter vector x). The Jacobian matrix plays an important role in most computational algorithms for estimating parameter values for nonlinear regression problems, in particular in the Gauss-Newton and Levenberg-Marquardt algorithms; see also Nonlinear Estimation for details.