This class represents a geometric variance gamma process \(S(t)\) (see. More...
Public Member Functions | |
| GeometricVarianceGammaProcess (double s0, double theta, double sigma, double nu, double mu, RandomStream stream) | |
| Constructs a new GeometricVarianceGammaProcess with parameters. | |
| GeometricVarianceGammaProcess (double s0, double mu, VarianceGammaProcess vargamma) | |
| Constructs a new GeometricVarianceGammaProcess. | |
| double | nextObservation () |
| Generates and returns the next observation \(X(t_j)\) of the stochastic process. | |
| double[] | generatePath () |
| Generates, returns, and saves the sample path \(\{X(t_0), X(t_1), \dots,
X(t_d)\}\). | |
| void | resetStartProcess () |
| Resets the GeometricaVarianceGammaProcess, but also applies the resetStartProcess method to the VarianceGammaProcess object used to generate this process. | |
| void | setParams (double s0, double theta, double sigma, double nu, double mu) |
| Sets the parameters \(S(t_0) = \mathtt{s0}\), \(\theta=
\mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and \(\mu= \mathtt{mu}\) of the process. | |
| double | getTheta () |
| Returns the value of the parameter \(\theta\). | |
| double | getMu () |
| Returns the value of the parameter \(\mu\). | |
| double | getNu () |
| Returns the value of the parameter \(\nu\). | |
| double | getSigma () |
| Returns the value of the parameter \(\sigma\). | |
| double | getOmega () |
Returns the value of the quantity \(\omega\) defined in ( omegaEqn ). | |
| VarianceGammaProcess | getVarianceGammaProcess () |
| Returns a reference to the variance gamma process \(X\) defined in the constructor. | |
| void | setStream (RandomStream stream) |
| Resets the random stream of the underlying generator to stream. | |
| RandomStream | getStream () |
| Returns the random stream of the underlying generator. | |
| Public Member Functions inherited from umontreal.ssj.stochprocess.StochasticProcess | |
| void | setObservationTimes (double[] T, int d) |
| Sets the observation times of the process to a copy of T, with. | |
| 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 class represents a geometric variance gamma process \(S(t)\) (see.
[167] (page 86)). This stochastic process is defined by the equation
\[ S(t) = S(0) \mbox{ exp}(\mu t + X(t; \sigma, \nu, \theta) + \omega t), \tag{GeoVGeqn} \]
where \(X\) is a variance gamma process and
\[ \omega= (1/\nu) \mbox{ ln}( 1 - \theta\nu- \sigma^2 \nu/2). \tag{omegaEqn} \]
Definition at line 44 of file GeometricVarianceGammaProcess.java.
Constructor & Destructor Documentation
◆ GeometricVarianceGammaProcess() [1/2]
| umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.GeometricVarianceGammaProcess | ( | double | s0, |
| double | theta, | ||
| double | sigma, | ||
| double | nu, | ||
| double | mu, | ||
| RandomStream | stream ) |
Constructs a new GeometricVarianceGammaProcess with parameters.
\(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\), \(\mu= \mathtt{mu}\) and initial value \(S(t_0) =
\mathtt{s0}\). The stream is used to generate the VarianceGammaProcess object used to implement \(X\) in ( GeoVGeqn ).
Definition at line 59 of file GeometricVarianceGammaProcess.java.
◆ GeometricVarianceGammaProcess() [2/2]
| umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.GeometricVarianceGammaProcess | ( | double | s0, |
| double | mu, | ||
| VarianceGammaProcess | vargamma ) |
Constructs a new GeometricVarianceGammaProcess.
The parameters
\(\theta, \sigma, \nu\) are set to the parameters of the VarianceGammaProcess vargamma. The parameter \(\mu\) is set to mu and the initial values \(S(t_0) = \mathtt{s0}\).
Definition at line 72 of file GeometricVarianceGammaProcess.java.
Member Function Documentation
◆ generatePath()
| double[] umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.generatePath | ( | ) |
Generates, returns, and saves the sample path \(\{X(t_0), X(t_1), \dots, X(t_d)\}\).
It can then be accessed via getPath, getSubpath, or getObservation. The generation method depends on the process type.
Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.
Definition at line 89 of file GeometricVarianceGammaProcess.java.
◆ getMu()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getMu | ( | ) |
Returns the value of the parameter \(\mu\).
Definition at line 182 of file GeometricVarianceGammaProcess.java.
◆ getNu()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getNu | ( | ) |
Returns the value of the parameter \(\nu\).
Definition at line 189 of file GeometricVarianceGammaProcess.java.
◆ getOmega()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getOmega | ( | ) |
Returns the value of the quantity \(\omega\) defined in ( omegaEqn ).
Definition at line 204 of file GeometricVarianceGammaProcess.java.
◆ getSigma()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getSigma | ( | ) |
Returns the value of the parameter \(\sigma\).
Definition at line 196 of file GeometricVarianceGammaProcess.java.
◆ getStream()
| RandomStream umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getStream | ( | ) |
Returns the random stream of the underlying generator.
Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.
Definition at line 240 of file GeometricVarianceGammaProcess.java.
◆ getTheta()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getTheta | ( | ) |
Returns the value of the parameter \(\theta\).
Definition at line 175 of file GeometricVarianceGammaProcess.java.
◆ getVarianceGammaProcess()
| VarianceGammaProcess umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.getVarianceGammaProcess | ( | ) |
Returns a reference to the variance gamma process \(X\) defined in the constructor.
Definition at line 212 of file GeometricVarianceGammaProcess.java.
◆ nextObservation()
| double umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.nextObservation | ( | ) |
Generates and returns the next observation \(X(t_j)\) of the stochastic process.
The processes are usually sampled sequentially, i.e. if the last observation generated was for time
\(t_{j-1}\), the next observation returned will be for time \(t_j\). In some cases, subclasses extending this abstract class may use non-sequential sampling algorithms (such as bridge sampling). The order of generation of the \(t_j\)’s is then specified by the subclass. All the processes generated using principal components analysis (PCA) do not have this method.
Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.
Definition at line 77 of file GeometricVarianceGammaProcess.java.
◆ resetStartProcess()
| void umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.resetStartProcess | ( | ) |
Resets the GeometricaVarianceGammaProcess, but also applies the resetStartProcess method to the VarianceGammaProcess object used to generate this process.
Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.
Definition at line 149 of file GeometricVarianceGammaProcess.java.
◆ setParams()
| void umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.setParams | ( | double | s0, |
| double | theta, | ||
| double | sigma, | ||
| double | nu, | ||
| double | mu ) |
Sets the parameters \(S(t_0) = \mathtt{s0}\), \(\theta= \mathtt{theta}\), \(\sigma= \mathtt{sigma}\), \(\nu= \mathtt{nu}\) and \(\mu= \mathtt{mu}\) of the process.
Warning: This method will recompute some quantities stored internally, which may be slow if called repeatedly.
Definition at line 162 of file GeometricVarianceGammaProcess.java.
◆ setStream()
| void umontreal.ssj.stochprocess.GeometricVarianceGammaProcess.setStream | ( | RandomStream | stream | ) |
Resets the random stream of the underlying generator to stream.
Reimplemented from umontreal.ssj.stochprocess.StochasticProcess.
Definition at line 236 of file GeometricVarianceGammaProcess.java.
The documentation for this class was generated from the following file:
- src/main/java/umontreal/ssj/stochprocess/GeometricVarianceGammaProcess.java
