Package | Description |
---|---|
net.finmath.montecarlo |
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.
|
net.finmath.montecarlo.automaticdifferentiation.backward |
Provides the implementation of backward automatic differentiation.
|
net.finmath.montecarlo.automaticdifferentiation.forward |
Provides the implementation of forward automatic differentiation.
|
net.finmath.stochastic |
Interfaces specifying operations on random variables.
|
Modifier and Type | Method and Description |
---|---|
RandomVariable |
RandomVariableLazyEvaluation.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
RandomVariable |
RandomVariableFromDoubleArray.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
RandomVariable |
RandomVariableFromFloatArray.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
Modifier and Type | Method and Description |
---|---|
RandomVariable |
RandomVariableDifferentiableAAD.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
Modifier and Type | Method and Description |
---|---|
RandomVariable |
RandomVariableDifferentiableAD.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
Modifier and Type | Method and Description |
---|---|
RandomVariable |
RandomVariable.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.
|
RandomVariable |
RandomVariableArrayImplementation.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
RandomVariable |
Scalar.apply(DoubleTernaryOperator operator,
RandomVariable argument1,
RandomVariable argument2) |
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