Module net.finmath.lib

Package net.finmath.montecarlo

Interface IndependentIncrements

All Known Subinterfaces:

BrownianMotion

All Known Implementing Classes:

BrownianBridge, BrownianMotionFromMersenneRandomNumbers, BrownianMotionFromRandomNumberGenerator, BrownianMotionLazyInit, BrownianMotionView, BrownianMotionWithControlVariate, CorrelatedBrownianMotion, GammaProcess, IndependentIncrementsFromICDF, JumpProcessIncrements, MertonJumpProcess, VarianceGammaProcess

public interface IndependentIncrements

Interface description of a time-discrete n-dimensional stochastic process \( X = (X_{1},\ldots,X_{n}) \) provided by independent increments \( \Delta X(t_{i}) = X(t_{i+1})-X(t_{i}) \). Here the dimension n is called factors since this process is used to generate multi-dimensional multi-factor processes and there one might use a different number of factors to generate processes of different dimension.

Version:

1.3

Author:

Christian Fries

Method Summary

Modifier and Type	Method	Description
IndependentIncrements	getCloneWithModifiedSeed(int seed)	Return a new object implementing BrownianMotion having the same specifications as this object but a different seed for the random number generator.
IndependentIncrements	getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization)	Return a new object implementing BrownianMotion having the same specifications as this object but a different time discretization.
default RandomVariable[]	getIncrement(int timeIndex)	Return the increment for a given timeIndex.
RandomVariable	getIncrement(int timeIndex, int factor)	Return the increment for a given timeIndex and given factor.
int	getNumberOfFactors()	Returns the number of factors.
int	getNumberOfPaths()	Returns the number of paths.
RandomVariable	getRandomVariableForConstant(double value)	Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.
TimeDiscretization	getTimeDiscretization()	Returns the time discretization used for this set of time-discrete Brownian increments.

Method Detail

getIncrement

default RandomVariable[] getIncrement(int timeIndex)

Return the increment for a given timeIndex. The method returns the random variable vector Δ X(t_i) := X(t_i+1)-X(t_i) for the given time index i.

Parameters:

timeIndex - The time index (corresponding to the this class's time discretization)

Returns:

The vector-valued increment (as a vector (array) of random variables).

getIncrement

RandomVariable getIncrement(int timeIndex,
                            int factor)

Return the increment for a given timeIndex and given factor. The method returns the random variable Δ X_j(t_i) := X_j(t_i+1)-X(t_i) for the given time index i and a given factor (index) j

Parameters:

timeIndex - The time index (corresponding to the this class's time discretization)

factor - The index of the factor (independent scalar increment)

Returns:

The factor (component) of the increments (a random variable)

getTimeDiscretization

TimeDiscretization getTimeDiscretization()

Returns the time discretization used for this set of time-discrete Brownian increments.

Returns:

The time discretization used for this set of time-discrete Brownian increments.

getNumberOfFactors

int getNumberOfFactors()

Returns the number of factors.

Returns:

The number of factors.

getNumberOfPaths

int getNumberOfPaths()

Returns the number of paths.

Returns:

The number of paths.

getRandomVariableForConstant

RandomVariable getRandomVariableForConstant(double value)

Returns a random variable which is initialized to a constant, but has exactly the same number of paths or discretization points as the ones used by this BrownianMotion.

Parameters:

value - The constant value to be used for initialized the random variable.

Returns:

A new random variable.

getCloneWithModifiedSeed

IndependentIncrements getCloneWithModifiedSeed(int seed)

Return a new object implementing BrownianMotion having the same specifications as this object but a different seed for the random number generator. This method is useful if you like to make Monte-Carlo samplings by changing the seed.

Parameters:

seed - New value for the seed.

Returns:

New object implementing BrownianMotion.

getCloneWithModifiedTimeDiscretization

IndependentIncrements getCloneWithModifiedTimeDiscretization(TimeDiscretization newTimeDiscretization)

Return a new object implementing BrownianMotion having the same specifications as this object but a different time discretization.

Parameters:

newTimeDiscretization - New time discretization

Returns:

New object implementing BrownianMotion.