This class differs from GammaProcessBridge only in that it requires the number of interval of the path to be a power of 2 and of equal size. More...
Public Member Functions | |
| GammaProcessSymmetricalBridge (double s0, double mu, double nu, RandomStream stream) | |
| Constructs a new GammaProcessSymmetricalBridge with parameters. | |
| GammaProcessSymmetricalBridge (double s0, double mu, double nu, GammaGen Ggen, BetaSymmetricalGen BSgen) | |
| Constructs a new GammaProcessSymmetricalBridge with parameters. | |
| double | nextObservation () |
| Generates and returns the next observation \(X(t_j)\) of the stochastic process. | |
| double | nextObservation (double nextT) |
| Generates and returns the next observation at time \(t_{j+1} =
\mathtt{nextTime}\), using the previous observation time \(t_j\) defined earlier (either by this method or by setObservationTimes), as well as the value of the previous observation \(X(t_j)\). | |
| double[] | generatePath () |
| Generates, returns and saves the path \(\{X(t_0), X(t_1), …, X(t_d)\}\). | |
| double[] | generatePath (double[] uniform01) |
| Generates, returns and saves the path \( \{X(t_0), X(t_1), …, X(t_d)\}\). | |
| Public Member Functions inherited from umontreal.ssj.stochprocess.GammaProcessBridge | |
| GammaProcessBridge (double s0, double mu, double nu, RandomStream stream) | |
| Constructs a new GammaProcessBridge with parameters \(\mu=
\mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) =
\mathtt{s0}\). | |
| GammaProcessBridge (double s0, double mu, double nu, GammaGen Ggen, BetaGen Bgen) | |
| Constructs a new GammaProcessBridge. | |
| void | resetStartProcess () |
| Resets the observation counter to its initial value \(j=0\), so that the current observation \(X(t_j)\) becomes \(X(t_0)\). | |
| void | setStream (RandomStream stream) |
| Resets the umontreal.ssj.rng.RandomStream of the. | |
| Public Member Functions inherited from umontreal.ssj.stochprocess.GammaProcess | |
| GammaProcess (double s0, double mu, double nu, RandomStream stream) | |
| Constructs a new GammaProcess with parameters \(\mu=
\mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) =
\mathtt{s0}\). | |
| GammaProcess (double s0, double mu, double nu, GammaGen Ggen) | |
| Constructs a new GammaProcess with parameters \(\mu=
\mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) =
\mathtt{s0}\). | |
| void | setParams (double s0, double mu, double nu) |
| Sets the parameters \(S(t_0) = \mathtt{s0}\), \(\mu= \mathtt{mu}\) and \(\nu= \mathtt{nu}\) of the process. | |
| double | getMu () |
| Returns the value of the parameter \(\mu\). | |
| double | getNu () |
| Returns the value of the parameter \(\nu\). | |
| RandomStream | getStream () |
| Returns the umontreal.ssj.rng.RandomStream stream. | |
| 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 differs from GammaProcessBridge only in that it requires the number of interval of the path to be a power of 2 and of equal size.
It is then possible to generate the bridge process using a special implementation of the beta random variate generator (using the symmetrical beta distribution) that is much faster (HOW MUCH? QUANTIFY!) than the general case. Note that when the method setObservationTimes is called, the equality of the size of the time steps is verified. To allow for differences due to floating point errors, time steps are considered to be equal if their relative difference is less than \(10^{-15}\).
Definition at line 44 of file GammaProcessSymmetricalBridge.java.
Constructor & Destructor Documentation
◆ GammaProcessSymmetricalBridge() [1/2]
| umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.GammaProcessSymmetricalBridge | ( | double | s0, |
| double | mu, | ||
| double | nu, | ||
| RandomStream | stream ) |
Constructs a new GammaProcessSymmetricalBridge with parameters.
\(\mu= \mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). The random variables are created using the umontreal.ssj.rng.RandomStream stream. Note that the same umontreal.ssj.rng.RandomStream stream is used for the umontreal.ssj.randvar.GammaGen and for the umontreal.ssj.randvar.BetaSymmetricalGen inluded in this class.
Definition at line 57 of file GammaProcessSymmetricalBridge.java.
◆ GammaProcessSymmetricalBridge() [2/2]
| umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.GammaProcessSymmetricalBridge | ( | double | s0, |
| double | mu, | ||
| double | nu, | ||
| GammaGen | Ggen, | ||
| BetaSymmetricalGen | BSgen ) |
Constructs a new GammaProcessSymmetricalBridge with parameters.
\(\mu= \mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\). Note that the umontreal.ssj.rng.RandomStream included in the umontreal.ssj.randvar.BetaSymmetricalGen is sets to the one included in the umontreal.ssj.randvar.GammaGen to avoid confusion. This umontreal.ssj.rng.RandomStream is then used to generate all the random variables.
Definition at line 73 of file GammaProcessSymmetricalBridge.java.
Member Function Documentation
◆ generatePath() [1/2]
| double[] umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.generatePath | ( | ) |
Generates, returns and saves the path \(\{X(t_0), X(t_1), …, X(t_d)\}\).
The gamma variates \(X\) in ( GammaEqn ) are generated using the
umontreal.ssj.rng.RandomStream stream or the umontreal.ssj.rng.RandomStream included in the umontreal.ssj.randvar.GammaGen Ggen.
Reimplemented from umontreal.ssj.stochprocess.GammaProcessBridge.
Definition at line 138 of file GammaProcessSymmetricalBridge.java.
◆ generatePath() [2/2]
| double[] umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.generatePath | ( | double[] | uniform01 | ) |
Generates, returns and saves the path \( \{X(t_0), X(t_1), …, X(t_d)\}\).
This method does not use the
umontreal.ssj.rng.RandomStream stream nor the umontreal.ssj.randvar.GammaGen Ggen. It uses the vector of uniform random numbers \(U(0, 1)\) provided by the user and generates the path by inversion. The vector uniform01 must be of dimension \(d\).
Reimplemented from umontreal.ssj.stochprocess.GammaProcessBridge.
Definition at line 158 of file GammaProcessSymmetricalBridge.java.
◆ nextObservation() [1/2]
| double umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.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.GammaProcessBridge.
Definition at line 79 of file GammaProcessSymmetricalBridge.java.
◆ nextObservation() [2/2]
| double umontreal.ssj.stochprocess.GammaProcessSymmetricalBridge.nextObservation | ( | double | nextT | ) |
Generates and returns the next observation at time \(t_{j+1} = \mathtt{nextTime}\), using the previous observation time \(t_j\) defined earlier (either by this method or by setObservationTimes), as well as the value of the previous observation \(X(t_j)\).
Warning: This method will reset the observations time \(t_{j+1}\) for this process to nextT. The user must make sure that the \(t_{j+1}\) supplied is \(\geq t_j\).
Reimplemented from umontreal.ssj.stochprocess.GammaProcessBridge.
Definition at line 106 of file GammaProcessSymmetricalBridge.java.
The documentation for this class was generated from the following file:
- src/main/java/umontreal/ssj/stochprocess/GammaProcessSymmetricalBridge.java
