Uses of Interface
net.finmath.functions.DoubleTernaryOperator
Package
Description
Provides basic interfaces and classes used in Monte-Carlo models (like LIBOR market model or Monte-Carlo simulation
of a Black-Scholes model), e.g., the Monte-Carlo random variable and the Brownian motion.
Provides the implementation of backward automatic differentiation.
Provides the implementation of forward automatic differentiation.
Interfaces specifying operations on random variables.
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Uses of DoubleTernaryOperator in net.finmath.montecarlo
Modifier and TypeMethodDescriptionRandomVariableFromDoubleArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableFromFloatArray.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) RandomVariableLazyEvaluation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) -
Uses of DoubleTernaryOperator in net.finmath.montecarlo.automaticdifferentiation.backward
Modifier and TypeMethodDescriptionRandomVariableDifferentiableAAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) -
Uses of DoubleTernaryOperator in net.finmath.montecarlo.automaticdifferentiation.forward
Modifier and TypeMethodDescriptionRandomVariableDifferentiableAD.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) -
Uses of DoubleTernaryOperator in net.finmath.stochastic
Modifier and TypeMethodDescriptionRandomVariable.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Applies x → operator(x,y,z) to this random variable, where x is this random variable and y and z are given random variable.RandomVariableArrayImplementation.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2) Scalar.apply
(DoubleTernaryOperator operator, RandomVariable argument1, RandomVariable argument2)