A Brownian motion process \(\{X(t) : t \geq0 \}\) sampled using the principal component decomposition (PCA) [69], [95], [153] . More...
Inheritance diagram for BrownianMotionPCA:
Collaboration diagram for BrownianMotionPCA:
Public Member Functions | |
| BrownianMotionPCA (double x0, double mu, double sigma, RandomStream stream) | |
Constructs a new BrownianMotionBridge with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\) and initial value \(X(t_0) = \mathtt{x0}\). More... | |
| BrownianMotionPCA (double x0, double mu, double sigma, NormalGen gen) | |
Constructs a new BrownianMotionBridge with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\) and initial value \(X(t_0) = \mathtt{x0}\). More... | |
| double | nextObservation () |
| void | setParams (double x0, double mu, double sigma) |
| double [] | generatePath () |
| double [] | generatePath (double[] uniform01) |
| double [][] | decompPCA (double[][] sigma) |
| double [] | getSortedEigenvalues () |
| Returns the sorted eigenvalues obtained in the PCA decomposition. | |
 Public Member Functions inherited from BrownianMotion | |
| BrownianMotion (double x0, double mu, double sigma, RandomStream stream) | |
Constructs a new BrownianMotion with parameters \(\mu=\) mu, \(\sigma=\) sigma and initial value \(X(t_0) =\) x0. More... | |
| BrownianMotion (double x0, double mu, double sigma, NormalGen gen) | |
Constructs a new BrownianMotion with parameters \(\mu=\) mu, \(\sigma=\) sigma and initial value \(X(t_0) =\) x0. More... | |
| double | nextObservation () |
| double | nextObservation (double nextTime) |
Generates and returns the next observation at time \(t_{j+1} =\) nextTime. More... | |
| double | nextObservation (double x, double dt) |
Generates an observation of the process in dt time units, assuming that the process has value \(x\) at the current time. More... | |
| double [] | generatePath () |
| double [] | generatePath (double[] uniform01) |
| Same as generatePath(), but a vector of uniform random numbers must be provided to the method. More... | |
| double [] | generatePath (RandomStream stream) |
| void | setParams (double x0, double mu, double sigma) |
| Resets the parameters \(X(t_0) = \mathtt{x0}\), \(\mu= \mathtt{mu}\) and \(\sigma= \mathtt{sigma}\) of the process. More... | |
| void | setStream (RandomStream stream) |
Resets the random stream of the normal generator to stream. | |
| RandomStream | getStream () |
| Returns the random stream of the normal generator. | |
| double | getMu () |
| Returns the value of \(\mu\). | |
| double | getSigma () |
| Returns the value of \(\sigma\). | |
| NormalGen | getGen () |
| Returns the normal random variate generator used. More... | |
| 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... | |
Protected Member Functions | |
| void | init () |
| Protected Member Functions inherited from BrownianMotion | |
| void | init () |
| Protected Member Functions inherited from StochasticProcess | |
| void | init () |
Protected Attributes | |
| double [][] | sigmaCov |
| double [][] | A |
| double [] | z |
| double [] | sortedEigenvalues |
| boolean | isDecompPCA |
| Protected Attributes inherited from BrownianMotion | |
| NormalGen | gen |
| double | mu |
| double [] | mudt |
| 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 |
Additional Inherited Members | |
| Package Attributes inherited from BrownianMotion | |
| double | sigma |
| double [] | sigmasqrdt |
Detailed Description
A Brownian motion process \(\{X(t) : t \geq0 \}\) sampled using the principal component decomposition (PCA) [69], [95], [153] .
Constructor & Destructor Documentation
◆ BrownianMotionPCA() [1/2]
| BrownianMotionPCA | ( | double | x0, |
| double | mu, | ||
| double | sigma, | ||
| RandomStream | stream | ||
| ) |
Constructs a new BrownianMotionBridge with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\) and initial value \(X(t_0) = \mathtt{x0}\).
The normal variates will be generated by inversion using stream.
◆ BrownianMotionPCA() [2/2]
| BrownianMotionPCA | ( | double | x0, |
| double | mu, | ||
| double | sigma, | ||
| NormalGen | gen | ||
| ) |
Constructs a new BrownianMotionBridge with parameters \(\mu= \mathtt{mu}\), \(\sigma= \mathtt{sigma}\) and initial value \(X(t_0) = \mathtt{x0}\).
The normal variates will be generated by gen.
The documentation for this class was generated from the following file:
- BrownianMotionPCA.java
