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

Packages that use StochasticLevenbergMarquardt.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 StochasticLevenbergMarquardt.RegularizationMethod in net.finmath.optimizer

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

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

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

Modifier and Type	Method	Description
static StochasticLevenbergMarquardt.RegularizationMethod	StochasticLevenbergMarquardt.RegularizationMethod.valueOf(String name)	Returns the enum constant of this type with the specified name.
static StochasticLevenbergMarquardt.RegularizationMethod[]	StochasticLevenbergMarquardt.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 StochasticLevenbergMarquardt.RegularizationMethod

Modifier	Constructor	Description
	StochasticLevenbergMarquardt(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, int numberOfThreads)	Create a Levenberg-Marquardt solver.
	StochasticLevenbergMarquardt(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService)	Create a Levenberg-Marquardt solver.
	StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService)
	StochasticLevenbergMarquardtAD(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, RandomVariable[] initialParameters, RandomVariable[] targetValues, RandomVariable[] parameterSteps, int maxIteration, double errorTolerance, ExecutorService executorService, boolean isGradientValuationParallel)
	StochasticOptimizerFactoryLevenbergMarquardt(StochasticLevenbergMarquardt.RegularizationMethod regularizationMethod, int maxIterations, double errorTolerance, int maxThreads)