SSJ  3.3.1
Stochastic Simulation in Java
Public Member Functions | List of all members
VarianceGammaProcessDiffPCASymmetricalBridge Class Reference

Same as VarianceGammaProcessDiff, but the two inner GammaProcess ’es are of the PCASymmetricalBridge type. More...

Inheritance diagram for VarianceGammaProcessDiffPCASymmetricalBridge:
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Collaboration diagram for VarianceGammaProcessDiffPCASymmetricalBridge:
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Public Member Functions

 VarianceGammaProcessDiffPCASymmetricalBridge (double s0, double theta, double sigma, double nu, RandomStream stream)
 Constructs a new VarianceGammaProcessDiffPCASymmetricalBridge with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). More...
 
- Public Member Functions inherited from VarianceGammaProcessDiffPCA
 VarianceGammaProcessDiffPCA (double s0, double theta, double sigma, double nu, RandomStream stream)
 Constructs a new VarianceGammaProcessDiffPCA with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). More...
 
 VarianceGammaProcessDiffPCA (double s0, double theta, double sigma, double nu, GammaProcessPCA gpos, GammaProcessPCA gneg)
 Constructs a new VarianceGammaProcessDiffPCA with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). More...
 
double nextObservation ()
 This method is not implemented is this class since the path cannot be generated sequentially.
 
double [] generatePath ()
 
double [] generatePath (double[] uniform01)
 
- Public Member Functions inherited from VarianceGammaProcessDiff
 VarianceGammaProcessDiff (double s0, double theta, double sigma, double nu, RandomStream stream)
 Constructs a new VarianceGammaProcessDiff with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). More...
 
 VarianceGammaProcessDiff (double s0, double theta, double sigma, double nu, GammaProcess gpos, GammaProcess gneg)
 The parameters of the GammaProcess objects for \(\Gamma^+\) and \(\Gamma^-\) are set to those of ( dblGammaParams ) and their initial values \(\Gamma^+(t_0)\) and \(\Gamma^-(t_0)\) are set to \(t_0\). More...
 
double nextObservation ()
 
double [] generatePath ()
 Generates, returns and saves the path. More...
 
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. More...
 
void resetStartProcess ()
 Sets the observation times on the VarianceGammaProcessDiff as usual, but also applies the resetStartProcess method to the two GammaProcess objects used to generate this process.
 
GammaProcess getGpos ()
 Returns a reference to the GammaProcess object gpos used to generate the \(\Gamma^+\) component of the process.
 
GammaProcess getGneg ()
 Returns a reference to the GammaProcess object gneg used to generate the \(\Gamma^-\) component of the process.
 
void setObservationTimes (double t[], int d)
 Sets the observation times on the VarianceGammaProcesDiff as usual, but also sets the observation times of the underlying GammaProcess ’es.
 
RandomStream getStream ()
 Returns the RandomStream of the \(\Gamma^+\) process.
 
void setStream (RandomStream stream)
 Sets the umontreal.ssj.rng.RandomStream of the two GammaProcess ’es to stream.
 
- Public Member Functions inherited from 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 \(S(t_0) = \mathtt{s0}\). More...
 
 VarianceGammaProcess (double s0, BrownianMotion BM, GammaProcess Gamma)
 Constructs a new VarianceGammaProcess. More...
 
double nextObservation ()
 Generates the observation for the next time. More...
 
double [] generatePath ()
 Generates and returns the path. More...
 
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. More...
 
void resetStartProcess ()
 Resets the observation index and counter to 0 and applies the resetStartProcess method to the BrownianMotion and the GammaProcess objects used to generate this process.
 
void setParams (double s0, double theta, double sigma, double nu)
 Sets the parameters \(S(t_0) =\) s0, \(\theta=\) theta, \(\sigma=\) sigma and \(\nu=\) nu of the process. More...
 
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. More...
 
void setStream (RandomStream stream)
 Resets the umontreal.ssj.rng.RandomStream ’s. More...
 
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 StochasticProcess
void setObservationTimes (double[] T, int d)
 Sets the observation times of the process to a copy of T, with. More...
 
void setObservationTimes (double delta, int d)
 Sets equidistant observation times at \(t_j = j\delta\), for. More...
 
double [] getObservationTimes ()
 Returns a reference to the array that contains the observation times. More...
 
int getNumObservationTimes ()
 Returns the number \(d\) of observation times, excluding the time \(t_0\).
 
abstract double [] generatePath ()
 Generates, returns, and saves the sample path \(\{X(t_0), X(t_1), \dots, X(t_d)\}\). More...
 
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 \(\{X(t_0), ... , X(t_d)\}\). More...
 
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. More...
 
double getObservation (int j)
 Returns \(X(t_j)\) from the current sample path. More...
 
void resetStartProcess ()
 Resets the observation counter to its initial value \(j=0\), so that the current observation \(X(t_j)\) becomes \(X(t_0)\). More...
 
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. More...
 
double nextObservation ()
 Generates and returns the next observation \(X(t_j)\) of the stochastic process. More...
 
int getCurrentObservationIndex ()
 Returns the value of the index \(j\) corresponding to the time. More...
 
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.
 
abstract void setStream (RandomStream stream)
 Resets the random stream of the underlying generator to stream.
 
abstract RandomStream getStream ()
 Returns the random stream of the underlying generator.
 
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 \(k\)-th observation to be generated for a sample path of this process. More...
 

Additional Inherited Members

- Protected Member Functions inherited from VarianceGammaProcessDiffPCA
void init ()
 
- Protected Member Functions inherited from VarianceGammaProcessDiff
void init ()
 
- Protected Member Functions inherited from VarianceGammaProcess
void init ()
 
- Protected Member Functions inherited from StochasticProcess
void init ()
 
- Protected Attributes inherited from VarianceGammaProcessDiff
GammaProcess gpos
 
GammaProcess gneg
 
double mup
 
- Protected Attributes inherited from VarianceGammaProcess
GammaProcess randomTime
 
BrownianMotion BM
 
double theta
 
- Protected Attributes inherited from StochasticProcess
boolean observationTimesSet = false
 
double x0 = 0.0
 
int d = -1
 
int observationIndex = 0
 
int observationCounter = 0
 
double [] t
 
double [] path
 
int [] observationIndexFromCounter
 
- Package Attributes inherited from VarianceGammaProcessDiffPCA
int [] indexEigenUp
 
int [] indexEigenDw
 
- Package Attributes inherited from VarianceGammaProcessDiff
double mun
 
double nup
 
double nun
 
- Package Attributes inherited from VarianceGammaProcess
double sigma
 
double nu
 

Detailed Description

Same as VarianceGammaProcessDiff, but the two inner GammaProcess ’es are of the PCASymmetricalBridge type.

Also, generatePath(double[] uniform01) distributes the lowest coordinates uniforms to the inner GammaProcessPCA according to their eigenvalues.

Constructor & Destructor Documentation

◆ VarianceGammaProcessDiffPCASymmetricalBridge()

VarianceGammaProcessDiffPCASymmetricalBridge ( double  s0,
double  theta,
double  sigma,
double  nu,
RandomStream  stream 
)

Constructs a new VarianceGammaProcessDiffPCASymmetricalBridge with parameters \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\).

There is only one umontreal.ssj.rng.RandomStream here which is used for the two inner GammaProcessPCASymmetricalBridge ’s. The other parameters are set as in VarianceGammaProcessDiff.


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