Package net.finmath.montecarlo.automaticdifferentiation.backward

package net.finmath.montecarlo.automaticdifferentiation.backward

Provides the implementation of backward automatic differentiation.

Author:

Christian Fries

Related Packages

Package	Description
net.finmath.montecarlo.automaticdifferentiation	Provides classes adding automatic differentiation capabilities to objects relying on RandomVariable objects.
net.finmath.montecarlo.automaticdifferentiation.backward.alternative	Provides alternative implementation of backward automatic differentiation.
net.finmath.montecarlo.automaticdifferentiation.forward	Provides the implementation of forward automatic differentiation.
net.finmath.montecarlo.automaticdifferentiation.forwardsensitivities	Provides method to obtain robust and fast forward sensitivites and hedge ratios.

Class	Description
RandomVariableDifferentiableAAD	Implementation of RandomVariableDifferentiable using the backward algorithmic differentiation (adjoint algorithmic differentiation, AAD).
RandomVariableDifferentiableAADFactory
RandomVariableDifferentiableAADFactory.DiracDeltaApproximationMethod