Module net.finmath.lib
Package net.finmath.montecarlo.process

Class LinearInterpolatedTimeDiscreteProcess

java.lang.Object
net.finmath.montecarlo.process.LinearInterpolatedTimeDiscreteProcess
All Implemented Interfaces:
Process
public class LinearInterpolatedTimeDiscreteProcess extends Object implements Process
A linear interpolated time discrete process, that is, given a collection of tuples (Double, RandomVariable) representing realizations \( X(t_{i}) \) this class implements the Process 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.
Version:
1.0
Author:
Christian Fries

  • Constructor Details

    • LinearInterpolatedTimeDiscreteProcess

      public LinearInterpolatedTimeDiscreteProcess(Map<Double,RandomVariable> 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 Details

    • add

      public LinearInterpolatedTimeDiscreteProcess add(LinearInterpolatedTimeDiscreteProcess process) throws CalculationException
      Create a new linear interpolated time discrete process by using the time discretization of this process and the sum of this process and the given one as its values.
      Parameters:
      process - A given process.
      Returns:
      A new process representing the of this and the given process.
      Throws:
      CalculationException - Thrown if the given process fails to evaluate at a certain time point.

    • 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 RandomVariable getProcessValue(double time, int component)
      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 \( X(t) \).

    • getProcessValue

      public RandomVariable getProcessValue(int timeIndex, int component)
      Description copied from interface: Process
      This method returns the realization of a component of the process for a given time index.
      Specified by:
      getProcessValue in interface Process
      Parameters:
      timeIndex - Time index at which the process should be observed.
      component - Component index of the process.
      Returns:
      The process component realizations (given as RandomVariableFromDoubleArray)

    • getMonteCarloWeights

      public RandomVariable getMonteCarloWeights(int timeIndex)
      Description copied from interface: Process
      This method returns the weights of a weighted Monte Carlo method (the probability density).
      Specified by:
      getMonteCarloWeights in interface Process
      Parameters:
      timeIndex - Time index at which the process should be observed
      Returns:
      A vector of positive weights which sums up to one

    • getNumberOfComponents

      public int getNumberOfComponents()
      Specified by:
      getNumberOfComponents in interface Process
      Returns:
      Returns the numberOfComponents.

    • getTimeDiscretization

      public TimeDiscretization getTimeDiscretization()
      Specified by:
      getTimeDiscretization in interface Process
      Returns:
      Returns the timeDiscretizationFromArray.

    • getTime

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

    • getTimeIndex

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

    • clone

      public Process clone()
      Description copied from interface: Process
      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 Process
      Overrides:
      clone in class Object
      Returns:
      Clone of the process