@hackage levmar0.1

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. See: http://www.ics.forth.gr/~lourakis/levmar/.

This library consists of two layers:

• LevMar.Intermediate: A medium-level layer that wraps the low-level functions from bindings-levmar to provide a more Haskell friendly interface.

• LevMar: A high-level layer that uses type-level programming to add extra type safety.

Each layer also has special data-fitting variants:

• LevMar.Intermediate.Fitting

• LevMar.Fitting

All modules are self-contained; i.e. each module re-exports all the things you need to work with it.

For an example how to use this library see Demo.hs which is included in this package. Demo.hs is a Haskell translation of lmdemo.c from the C levmar library.

A note regarding the 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.