bindings-levmar: Low level bindings to the C levmar (Levenberg-Marquardt) library
|Versions||0.1, 0.1.0.1, 0.1.1, 0.1.1.1, 0.2.0.1, 1.0, 220.127.116.11, 18.104.22.168, 1.1, 22.214.171.124, 126.96.36.199, 188.8.131.52, 184.108.40.206|
|Dependencies||base (>=3 && <4.7), bindings‑DSL (>=1.0.15 && <1.1) [details]|
|Copyright||2009–2012 Roel van Dijk & Bas van Dijk|
|Author||Roel van Dijk <firstname.lastname@example.org> & Bas van Dijk <email@example.com>|
|Maintainer||Roel van Dijk <firstname.lastname@example.org> & Bas van Dijk <email@example.com>|
|Source repo||head: git clone git://github.com/basvandijk/bindings-levmar.git|
|Uploaded||by BasVanDijk at Sun Sep 9 11:58:13 UTC 2012|
|Downloads||4798 total (35 in the last 30 days)|
|Rating||(no votes yet) [estimated by rule of succession]|
|Status||Docs uploaded by user
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levmar package for a high-level wrapper
around this package.
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.
Both unconstrained and constrained (under linear equations and box constraints) Levenberg-Marquardt variants are included. All functions have Double and Float variants.
Note that the included
is lightly patched to make it pure. This way the
functions can be used inside
A note regarding the license:
All files EXCEPT those in the levmar-2.4 directory fall under the BSD3 license. The levmar C library, which is bundled with this binding, falls under the GPL. If you build a program which is linked with this binding then it is also linked with levmar. This means such a program can only by distributed under the terms of the GPL.
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Link with Intel's MKL optimized libraries.
Use the accelerate framework for LAPACK/BLAS on OS X
Use -f <flag> to enable a flag, or -f -<flag> to disable that flag. More info
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