SSJ  3.3.1
Stochastic Simulation in Java
Public Member Functions | Protected Member Functions | Protected Attributes | Package Attributes | List of all members
BrownianMotionPCAEqualSteps Class Reference

Same as BrownianMotionPCA, but uses a trick to speed up the calculation when the time steps are equidistant. More...

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

 BrownianMotionPCAEqualSteps (double x0, double mu, double sigma, RandomStream stream)
 Constructs a new BrownianMotionPCAEqualSteps.
 
 BrownianMotionPCAEqualSteps (double x0, double mu, double sigma, NormalGen gen)
 Constructs a new BrownianMotionPCAEqualSteps.
 
double nextObservation ()
 
double [] generatePath ()
 
double [] generatePath (double[] QMCpointsBM)
 
void setObservationTimes (double[] t, int d)
 
void setObservationTimes (double dt, int d)
 
double [] getSortedEigenvalues ()
 
- 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 [][] A
 
double [] z
 
boolean isDecompPCA
 
double [] sortedEigenvalues
 
- 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
 

Package Attributes

double dt
 
- Package Attributes inherited from BrownianMotion
double sigma
 
double [] sigmasqrdt
 

Detailed Description

Same as BrownianMotionPCA, but uses a trick to speed up the calculation when the time steps are equidistant.


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