Uses of Class
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

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

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)