SSJ API Documentation
Stochastic Simulation in Java
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umontreal.ssj.stochprocess.VarianceGammaProcessAlternate Class Reference

This is a VarianceGammaProcess for which the successive random numbers are used in a different order to generate the sample path. More...

Inheritance diagram for umontreal.ssj.stochprocess.VarianceGammaProcessAlternate:
umontreal.ssj.stochprocess.VarianceGammaProcess umontreal.ssj.stochprocess.StochasticProcess

Public Member Functions

double[] generatePath ()
 Generates the sample path by using the uniform random numbers in an alternate way, and returns the path of the VG process.
Public Member Functions inherited from umontreal.ssj.stochprocess.VarianceGammaProcess
 VarianceGammaProcess (double s0, double theta, double sigma, double nu, RandomStream stream)
 Constructs a new VarianceGammaProcess with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\).
 VarianceGammaProcess (double s0, BrownianMotion BM, GammaProcess Gamma)
 Constructs a new VarianceGammaProcess.
double nextObservation ()
 Generates the observation for the next time.
double[] generatePath (double[] uniform01)
 Similar to the usual generatePath(), but here the uniform random numbers used for the simulation must be provided to the method.
void resetStartProcess ()
 Resets the observation index and counter to 0 and applies the resetStartProcess method to the BrownianMotion and the.
void setParams (double s0, double theta, double sigma, double nu)
 Sets the parameters \(S(t_0) =\) s0, \(\theta=\) theta,.
double getTheta ()
 Returns the value of the parameter \(\theta\).
double getSigma ()
 Returns the value of the parameter \(\sigma\).
double getNu ()
 Returns the value of the parameter \(\nu\).
void setObservationTimes (double t[], int d)
 Sets the observation times on the VarianceGammaProcess as usual, but also sets the observation times of the underlying GammaProcess.
void setStream (RandomStream stream)
 Resets the umontreal.ssj.rng.RandomStream ’s.
RandomStream getStream ()
 Returns the random stream of the BrownianMotion process, which should be the same as for the GammaProcess.
BrownianMotion getBrownianMotion ()
 Returns a reference to the inner BrownianMotion.
GammaProcess getGammaProcess ()
 Returns a reference to the inner GammaProcess.
Public Member Functions inherited from umontreal.ssj.stochprocess.StochasticProcess
void setObservationTimes (double delta, int d)
 Sets equidistant observation times at \(t_j = j\delta\), for.
double[] getObservationTimes ()
 Returns a reference to the array that contains the observation times.
int getNumObservationTimes ()
 Returns the number \(d\) of observation times, excluding the time \(t_0\).
double[] generatePath (RandomStream stream)
 Same as generatePath(), but first resets the stream to stream.
double[] getPath ()
 Returns a reference to the last generated sample path \(\{X(t_0), ... , X(t_d)\}\).
void getSubpath (double[] subpath, int[] pathIndices)
 Returns in subpath the values of the process at a subset of the observation times, specified as the times \(t_j\) whose indices.
double getObservation (int j)
 Returns \(X(t_j)\) from the current sample path.
boolean hasNextObservation ()
 Returns true if \(j<d\), where \(j\) is the number of observations of the current sample path generated since the last call to resetStartProcess.
int getCurrentObservationIndex ()
 Returns the value of the index \(j\) corresponding to the time.
double getCurrentObservation ()
 Returns the value of the last generated observation \(X(t_j)\).
double getX0 ()
 Returns the initial value \(X(t_0)\) for this process.
void setX0 (double s0)
 Sets the initial value \(X(t_0)\) for this process to s0, and reinitializes.
int[] getArrayMappingCounterToIndex ()
 Returns a reference to an array that maps an integer \(k\) to \(i_k\), the index of the observation \(S(t_{i_k})\) corresponding to the.

Detailed Description

This is a VarianceGammaProcess for which the successive random numbers are used in a different order to generate the sample path.

The first one is used for the first generated value of the gamma process, the second one for the first generated value of the Brownian process, the third one for the second generated value of the gamma process, the fourth one for the second value of the Brownian process, and so on. Only the order in which the uniform random numbers are used in the method generatePath differs. These numbers are generated at the beginning and then reordered. This can make a difference when we use RQMC methods.

Definition at line 18 of file VarianceGammaProcessAlternate.java.

Member Function Documentation

◆ generatePath()

double[] umontreal.ssj.stochprocess.VarianceGammaProcessAlternate.generatePath ( )

Generates the sample path by using the uniform random numbers in an alternate way, and returns the path of the VG process.

Reimplemented from umontreal.ssj.stochprocess.VarianceGammaProcess.

Definition at line 32 of file VarianceGammaProcessAlternate.java.


The documentation for this class was generated from the following file: