finMath lib documentation
net.finmath.montecarlo.process

Class LinearInterpolatedTimeDiscreteProcess

• java.lang.Object
• net.finmath.montecarlo.process.LinearInterpolatedTimeDiscreteProcess
• All Implemented Interfaces:
ProcessInterface

public class LinearInterpolatedTimeDiscreteProcess
extends Object
implements ProcessInterface
A linear interpolated time discrete process, that is, given a collection of tuples (Double, RandomVariable) representing realizations $$X(t_{i})$$ this class implements the ProcessInterface and creates a stochastic process $$t \mapsto X(t)$$ where $X(t) = \frac{t_{i+1} - t}{t_{i+1}-t_{i}} X(t_{i}) + \frac{t - t_{i}}{t_{i+1}-t_{i}} X(t_{i+1})$ with $$t_{i} \leq t \leq t_{i+1}$$. Note: this is the interpolation scheme used in the convergence of the Euler-Maruyama scheme.
Author:
Christian Fries
• Constructor Detail

• LinearInterpolatedTimeDiscreteProcess

public LinearInterpolatedTimeDiscreteProcess(Map<Double,RandomVariableInterface> realizations)
Create a time discrete process by linear interpolation of random variables.
Parameters:
realizations - Given map from time to random variable. The map must not be modified.
• Method Detail

• apply

public LinearInterpolatedTimeDiscreteProcess apply(DoubleUnaryOperator function)
Create a new process consisting of the interpolation of the random variables obtained by applying the given function to this process discrete set of random variables. That is $$t \mapsto Y(t)$$ where $Y(t) = \frac{t_{i+1} - t}{t_{i+1}-t_{i}} f(X(t_{i})) + \frac{t - t_{i}}{t_{i+1}-t_{i}} f(X(t_{i+1}))$ with $$t_{i} \leq t \leq t_{i+1}$$ and a given function $$f$$.
Parameters:
function - The function $$f$$, a univariate function.
Returns:
A new process consisting of the interpolation of the random variables obtained by applying the given function to this process discrete set of random variables.
• getProcessValue

public RandomVariableInterface getProcessValue(double time,
int component)
throws CalculationException
Returns the (possibly interpolated) value of this stochastic process at a given time $$t$$.
Parameters:
time - The time $$t$$.
component - The component to be returned (if this is a vector valued process), otherwise 0.
Returns:
The random variable $$X(t)$$.
Throws:
CalculationException - Thrown if this process fails to evaluate at the given time point.
• getProcessValue

public RandomVariableInterface getProcessValue(int timeIndex,
int component)
throws CalculationException
Description copied from interface: ProcessInterface
This method returns the realization of a component of the process for a given time index.
Specified by:
getProcessValue in interface ProcessInterface
Parameters:
timeIndex - Time index at which the process should be observed
component - Component index of the process
Returns:
The process component realizations (given as RandomVariable)
Throws:
CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
• getMonteCarloWeights

public RandomVariableInterface getMonteCarloWeights(int timeIndex)
throws CalculationException
Description copied from interface: ProcessInterface
This method returns the weights of a weighted Monte Carlo method (the probability density).
Specified by:
getMonteCarloWeights in interface ProcessInterface
Parameters:
timeIndex - Time index at which the process should be observed
Returns:
A vector of positive weights which sums up to one
Throws:
CalculationException - Thrown if the valuation fails, specific cause may be available via the cause() method.
• getTime

public double getTime(int timeIndex)
Specified by:
getTime in interface ProcessInterface
Parameters:
timeIndex - Time index.
Returns:
Returns the time for a given time index.
• getTimeIndex

public int getTimeIndex(double time)
Description copied from interface: ProcessInterface
Returns the time index for a given simulation time.
Specified by:
getTimeIndex in interface ProcessInterface
Parameters:
time - The given simulation time.
Returns:
Returns the time index for a given time
• clone

public ProcessInterface clone()
Description copied from interface: ProcessInterface
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.
Specified by:
clone in interface ProcessInterface
Overrides:
clone in class Object
Returns:
Clone of the process