Uses of Class
net.finmath.optimizer.LevenbergMarquardt

Packages that use LevenbergMarquardt

Package	Description
net.finmath.optimizer	This package provides classes with numerical algorithm for optimization of an objective function and a factory to easy construction of the optimizers.

Uses of LevenbergMarquardt in net.finmath.optimizer

Methods in net.finmath.optimizer that return LevenbergMarquardt

Modifier and Type	Method	Description
LevenbergMarquardt	LevenbergMarquardt.clone()	Create a clone of this LevenbergMarquardt optimizer.
LevenbergMarquardt	LevenbergMarquardt.getCloneWithModifiedTargetValues(double[] newTargetVaues, double[] newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.
LevenbergMarquardt	LevenbergMarquardt.getCloneWithModifiedTargetValues(List<Number> newTargetVaues, List<Number> newWeights, boolean isUseBestParametersAsInitialParameters)	Create a clone of this LevenbergMarquardt optimizer with a new vector for the target values and weights.
LevenbergMarquardt	LevenbergMarquardt.setErrorTolerance(double errorTolerance)	Set the error tolerance.
LevenbergMarquardt	LevenbergMarquardt.setInitialParameters(double[] initialParameters)	Set the initial parameters for the solver.
LevenbergMarquardt	LevenbergMarquardt.setLambda(double lambda)	Set the parameter λ used in the Tikhonov-like regularization of the Hessian matrix, that is the \( \lambda \) in \( H + \lambda \diag H \).
LevenbergMarquardt	LevenbergMarquardt.setMaxIteration(int maxIteration)	Set the maximum number of iterations to be performed until the solver gives up.
LevenbergMarquardt	LevenbergMarquardt.setParameterSteps(double[] parameterSteps)	Set the parameter step for the solver.
LevenbergMarquardt	LevenbergMarquardt.setTargetValues(double[] targetValues)	Set the target values for the solver.
LevenbergMarquardt	LevenbergMarquardt.setWeights(double[] weights)	Set the weight for the objective function.