Levenberg–Marquardt algorithm: Difference between revisions

Revision as of 10:30, 13 November 2004

Revision as of 11:13, 13 November 2004

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This minimization problem arises especially in [[least squares]] [[curve fitting]] (see also: [[nonlinear programming]]).

The Levenberg-Marquardt algorithm (LMA) interpolates between the [[Gauss-Newton algorithm]] (GNA) and the method of [[steepestgradient descent]]. The LMA is ''robuster'' than the GNA, which means that in many cases it finds a solution even if it starts very far off the final minimum. On the other hand, for well-behaved functions and reasonable starting parameters, the LMA tends to be a bit slower than the GNA. The LMA is the most popular curve-fitting algorithm; it is used in almost any software that provides a generic curve-fitting tool; few users will ever need another curve-fitting algorithm.

== The problem ==