levmar is a native ANSI C implementation of the Levenberg-Marquardt
optimization algorithm. Both unconstrained and constrained (under linear
equations, inequality and box constraints) Levenberg-Marquardt variants are
included. The LM algorithm is an iterative technique that finds a local
minimum of a function that is expressed as the sum of squares of nonlinear
functions. It has become a standard technique for nonlinear least-squares
problems and can be thought of as a combination of steepest descent and the
Gauss-Newton method. When the current solution is far from the correct on,
the algorithm behaves like a steepest descent method: slow, but guaranteed
to converge. When the current solution is close to the correct solution, it
becomes a Gauss-Newton method.