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An implementation of the Levenberg-Marquardt algorithm
Haskell Nix
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README.markdown

The Levenberg-Marquardt 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 one, 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.

Optional box- and linear constraints can be given. Both single and double precision floating point types are supported.

The actual algorithm is implemented in a C library which is bundled with bindings-levmar which this package depends on.

License

This library depends on bindings-levmar which is bundled together with a C library which falls under the GPL. Please be aware of this when distributing programs linked with this library. For details see the description and license of bindings-levmar.

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