ModifiedLevenbergMarquardtMinimizer Class

Class for minimizing the L2 norm of a function using the a modified Levenberg Marquardt algorithm.

Inheritance Hierarchy

SystemObject
CenterSpace.NMath.CoreModifiedLevenbergMarquardtMinimizer

Namespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.4

Syntax

C++

Copy

[SerializableAttribute]
public class ModifiedLevenbergMarquardtMinimizer : INonlinearLeastSqMinimizer, 
	ICloneable

<SerializableAttribute>
Public Class ModifiedLevenbergMarquardtMinimizer
	Implements INonlinearLeastSqMinimizer, ICloneable

[SerializableAttribute]
public ref class ModifiedLevenbergMarquardtMinimizer : INonlinearLeastSqMinimizer, 
	ICloneable

[<SerializableAttribute>]
type ModifiedLevenbergMarquardtMinimizer =  
    class
        interface INonlinearLeastSqMinimizer
        interface ICloneable
    end

The ModifiedLevenbergMarquardtMinimizer type exposes the following members.

Constructors

	Name	Description
	ModifiedLevenbergMarquardtMinimizer	Constructs a ModifiedLevenbergMarquardtMinimizer object from the given information.
	ModifiedLevenbergMarquardtMinimizer(Double)	Constructs a ModifiedLevenbergMarquardtMinimizer object from the given information.
	ModifiedLevenbergMarquardtMinimizer(Int32)	Constructs a ModifiedLevenbergMarquardtMinimizer object from the given information.
	ModifiedLevenbergMarquardtMinimizer(Int32, Double)	Constructs a ModifiedLevenbergMarquardtMinimizer object from the given information.

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Properties

	Name	Description
	FinalResidual	Gets the final L2 norm, or residual, of the function being minimized.
	GradientTolerance	Gets and sets the gradient tolerance. Iteration will stop \|\|Jk'*Fk\|\| is less than gradientTolerance, where Jk is value of the Jacobian at the kth iterate and Fk is the value of the objective function at the kth iterate.
	InitialResidual	Gets the residual associated with the starting point.
	Iterations	Gets the number of iterations performed.
	MaxIterations	Gets and sets the maximum number of iterations to perform.
	MaxIterationsMet	Returns true if the minimum just computed stopped because the maximum number of iterations was reached; otherwise, false.

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Methods

	Name	Description
	Clone	Returns a deep copy of self.
	Minimize(DoubleMultiVariableFunction, DoubleVector)	Minimizes the L2 norm of the given function near the given starting point.
	Minimize(DoubleMultiVariableFunction, DoubleVector, Double)	Minimizes the L2 norm of the given function near the given starting point.
	SetAllTolerances	Sets the gradient tolerance to the given value. Iteration will stop \|\|Jk'*Fk\|\| is less than gradientTolerance, where Jk is value of the Jacobian at the kth iterate and Fk is the value of the objective function at the kth iterate.

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Fields

	Name	Description
	DEFAULT_MAX_ITER	The default maximum number of iterations.
	DEFAULT_TOLERANCE	The default error tolerance to use for both gradient and solution delta

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Remarks

This is an implementaion of the algorithm described by Jinyan Fan in the paper: MATHEMATICS OF COMPUTATION Volume 81, Number 277, January 2012, Pages 447–466 S 0025-5718(2011)02496-8 THE MODIFIED LEVENBERG-MARQUARDT METHOD FOR NONLINEAR EQUATIONS WITH CUBIC CONVERGENCE

Reference

CenterSpace.NMath.Core Namespace