LevenbergMarquardtMinimizer - Math.NET Numerics Documentation

Namespaces

Types in MathNet.Numerics.Optimization

Constructors

LevenbergMarquardtMinimizer

Methods

Properties

Public Constructors

LevenbergMarquardtMinimizer(double initialMu, double gradientTolerance, double stepTolerance, double functionTolerance, int maximumIterations)

Public Methods

bool Equals(object obj)

NonlinearMinimizationResult FindMinimum(IObjectiveModel objective, Vector<T> initialGuess, Vector<T> lowerBound, Vector<T> upperBound, Vector<T> scales, List<bool> isFixed)

NonlinearMinimizationResult FindMinimum(IObjectiveModel objective, Double[] initialGuess, Double[] lowerBound, Double[] upperBound, Double[] scales, Boolean[] isFixed)

int GetHashCode()

Type GetType()

NonlinearMinimizationResult Minimum(IObjectiveModel objective, Vector<T> initialGuess, Vector<T> lowerBound, Vector<T> upperBound, Vector<T> scales, List<bool> isFixed, double initialMu, double gradientTolerance, double stepTolerance, double functionTolerance, int maximumIterations)

Non-linear least square fitting by the Levenberg-Marduardt algorithm.

Parameters

`IObjectiveModel` objective

The objective function, including model, observations, and parameter bounds.

`Vector<T>` initialGuess

The initial guess values.

`Vector<T>` lowerBound

`Vector<T>` upperBound

`Vector<T>` scales

`List<bool>` isFixed

`double` initialMu

The initial damping parameter of mu.

`double` gradientTolerance

The stopping threshold for infinity norm of the gradient vector.

`double` stepTolerance

The stopping threshold for L2 norm of the change of parameters.

`double` functionTolerance

The stopping threshold for L2 norm of the residuals.

`int` maximumIterations

The max iterations.

Return

`NonlinearMinimizationResult`

The result of the Levenberg-Marquardt minimization

string ToString()

Public Properties

double FunctionTolerance get; set;

double GradientTolerance get; set;

double InitialMu get; set;

The scale factor for initial mu