- All Superinterfaces:
Process
- All Known Implementing Classes:
EulerSchemeFromProcessModel
,MonteCarloProcessFromProcessModel
The interface for a process (numerical scheme) of a stochastic process X where
X = f(Y) and Y is an Itô process
\[ dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m} \] The parameters are provided by a model implementing
\[ dY_{j} = \mu_{j} dt + \lambda_{1,j} dW_{1} + \ldots + \lambda_{m,j} dW_{m} \] The parameters are provided by a model implementing
ProcessModel
:
- The value of Y(0) is provided by the method
ProcessModel.getInitialState(net.finmath.montecarlo.process.MonteCarloProcess)
. - The value of μ is provided by the method
ProcessModel.getDrift(net.finmath.montecarlo.process.MonteCarloProcess, int, net.finmath.stochastic.RandomVariable[], net.finmath.stochastic.RandomVariable[])
. - The value λj is provided by the method
ProcessModel.getFactorLoading(net.finmath.montecarlo.process.MonteCarloProcess, int, int, net.finmath.stochastic.RandomVariable[])
. - The function f is provided by the method
ProcessModel.applyStateSpaceTransform(net.finmath.montecarlo.process.MonteCarloProcess, int, int, net.finmath.stochastic.RandomVariable)
.
- Version:
- 1.0
- Author:
- Christian Fries
- See Also:
The definition of the model.
-
Method Summary
Modifier and TypeMethodDescriptionclone()
Create and return a clone of this process.getCloneWithModifiedData(Map<String,Object> dataModified)
Returns a clone of this model where the specified properties have been modified.Returns a clone of this model where the specified properties have been modified.int
int
Methods inherited from interface net.finmath.montecarlo.process.Process
getModel, getMonteCarloWeights, getNumberOfComponents, getProcessValue, getProcessValue, getTime, getTimeDiscretization, getTimeIndex
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Method Details
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getNumberOfPaths
int getNumberOfPaths()- Returns:
- Returns the numberOfPaths.
-
getNumberOfFactors
int getNumberOfFactors()- Returns:
- Returns the numberOfFactors.
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getStochasticDriver
IndependentIncrements getStochasticDriver()- Returns:
- Returns the stochastic driver used to generate this process
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getCloneWithModifiedModel
Returns a clone of this model where the specified properties have been modified. Note that there is no guarantee that a model reacts on a specification of a properties in the parameter mapdataModified
. If data is provided which is ignored by the model no exception may be thrown.- Parameters:
model
- The model to be used.- Returns:
- A clone of this model (or this model if no parameter was modified).
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getCloneWithModifiedData
Returns a clone of this model where the specified properties have been modified. Note that there is no guarantee that a model reacts on a specification of a properties in the parameter mapdataModified
. If data is provided which is ignored by the model no exception may be thrown.- Parameters:
dataModified
- Key-value-map of parameters to modify.- Returns:
- A clone of this model (or this model if no parameter was modified).
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clone
MonteCarloProcess clone()Create and return a clone of this process. The clone is not tied to any model, but has the same process specification, that is, if the model is the same, it would generate the same paths.
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