Uses of Enum
net.finmath.optimizer.LevenbergMarquardt.RegularizationMethod

Packages that use LevenbergMarquardt.RegularizationMethod

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.RegularizationMethod in net.finmath.optimizer

Subclasses with type arguments of type LevenbergMarquardt.RegularizationMethod in net.finmath.optimizer

Modifier and Type	Class	Description
static enum	LevenbergMarquardt.RegularizationMethod	The regularization method used to invert the approximation of the Hessian matrix.

Methods in net.finmath.optimizer that return LevenbergMarquardt.RegularizationMethod

Modifier and Type	Method	Description
static LevenbergMarquardt.RegularizationMethod	LevenbergMarquardt.RegularizationMethod.valueOf(String name)	Returns the enum constant of this type with the specified name.
static LevenbergMarquardt.RegularizationMethod[]	LevenbergMarquardt.RegularizationMethod.values()	Returns an array containing the constants of this enum type, in the order they are declared.

Constructors in net.finmath.optimizer with parameters of type LevenbergMarquardt.RegularizationMethod

Modifier	Constructor	Description
	LevenbergMarquardt(LevenbergMarquardt.RegularizationMethod regularizationMethod, double[] initialParameters, double[] targetValues, int maxIteration, int numberOfThreads)	Create a Levenberg-Marquardt solver.
	LevenbergMarquardt(LevenbergMarquardt.RegularizationMethod regularizationMethod, double[] initialParameters, double[] targetValues, int maxIteration, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
	OptimizerFactoryLevenbergMarquardt(LevenbergMarquardt.RegularizationMethod regularizationMethod, double lambda, int maxIterations, double errorTolerance, int maxThreads)
	OptimizerFactoryLevenbergMarquardt(LevenbergMarquardt.RegularizationMethod regularizationMethod, int maxIterations, double errorTolerance, int maxThreads)