Uses of Interface
net.finmath.montecarlo.automaticdifferentiation.RandomVariableDifferentiable
Packages that use RandomVariableDifferentiable
Package
Description
Provides classes adding automatic differentiation capabilities to objects relying on RandomVariable objects.
Provides the implementation of backward automatic differentiation.
Provides the implementation of forward automatic differentiation.
-
Uses of RandomVariableDifferentiable in net.finmath.montecarlo.automaticdifferentiation
Methods in net.finmath.montecarlo.automaticdifferentiation that return RandomVariableDifferentiableModifier and TypeMethodDescriptionAbstractRandomVariableDifferentiableFactory.createRandomVariable(double value)abstract RandomVariableDifferentiableAbstractRandomVariableDifferentiableFactory.createRandomVariable(double time, double value)abstract RandomVariableDifferentiableAbstractRandomVariableDifferentiableFactory.createRandomVariable(double time, double[] values)RandomVariableDifferentiableFactory.createRandomVariable(double value)Create a (deterministic) random variable from a constant.RandomVariableDifferentiableFactory.createRandomVariable(double time, double value)Create a (deterministic) random variable form a constant using a specific filtration time.RandomVariableDifferentiableFactory.createRandomVariable(double time, double[] values)Create a random variable form an array using a specific filtration time.default RandomVariableDifferentiableRandomVariableDifferentiable.getCloneIndependent()Returns a clone of this differentiable random variable with a new ID. -
Uses of RandomVariableDifferentiable in net.finmath.montecarlo.automaticdifferentiation.backward
Classes in net.finmath.montecarlo.automaticdifferentiation.backward that implement RandomVariableDifferentiableModifier and TypeClassDescriptionclassImplementation ofRandomVariableDifferentiableusing the backward algorithmic differentiation (adjoint algorithmic differentiation, AAD).Methods in net.finmath.montecarlo.automaticdifferentiation.backward that return RandomVariableDifferentiableModifier and TypeMethodDescriptionRandomVariableDifferentiableAADFactory.createRandomVariable(double time, double value)RandomVariableDifferentiableAADFactory.createRandomVariable(double time, double[] values)RandomVariableDifferentiableAAD.getCloneIndependent() -
Uses of RandomVariableDifferentiable in net.finmath.montecarlo.automaticdifferentiation.forward
Classes in net.finmath.montecarlo.automaticdifferentiation.forward that implement RandomVariableDifferentiableModifier and TypeClassDescriptionclassImplementation ofRandomVariableDifferentiableusing the forward algorithmic differentiation (AD).Methods in net.finmath.montecarlo.automaticdifferentiation.forward that return RandomVariableDifferentiableModifier and TypeMethodDescriptionRandomVariableDifferentiableADFactory.createRandomVariable(double time, double value)RandomVariableDifferentiableADFactory.createRandomVariable(double time, double[] values)