Same as GammaProcessPCA, but the generated uniforms correspond to a bridge transformation of the BrownianMotionPCA instead of a sequential transformation. More...

Inheritance diagram for umontreal.ssj.stochprocess.GammaProcessPCABridge:

Public Member Functions
	GammaProcessPCABridge (double s0, double mu, double nu, RandomStream stream)
	Constructs a new GammaProcessPCABridge with parameters \(\mu= \mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\).
double[]	generatePath (double[] uniform01)
	Generates, returns and saves the path \( \{X(t_0), X(t_1), …, X(t_d)\}\).
double[]	generatePath ()
	Generates, returns and saves the path \(\{X(t_0), X(t_1), …, X(t_d)\}\).
void	setParams (double s0, double mu, double nu)
	Sets the parameters s0, \(\mu\) and \(\nu\) to new values, and sets the variance parameters of the BrownianMotionPCA to \(\nu\).
void	setObservationTimes (double[] t, int d)
	Sets the observation times of the GammaProcessPCA and the.
BrownianMotionPCA	getBMPCA ()
	Returns the inner BrownianMotionPCA.
Public Member Functions inherited from umontreal.ssj.stochprocess.GammaProcessPCA
	GammaProcessPCA (double s0, double mu, double nu, RandomStream stream)
	Constructs a new GammaProcessPCA with parameters \(\mu= \mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\).
	GammaProcessPCA (double s0, double mu, double nu, GammaGen Ggen)
	Constructs a new GammaProcessPCA with parameters \(\mu= \mathtt{mu}\), \(\nu= \mathtt{nu}\) and initial value \(S(t_0) = \mathtt{s0}\).
double	nextObservation ()
	This method is not implemented in this class since the path cannot be generated sequentially.
double	nextObservation (double nextT)
	This method is not implemented in this class since the path cannot be generated sequentially.
void	setStream (RandomStream stream)
	Resets the umontreal.ssj.rng.RandomStream of the gamma generator and the umontreal.ssj.rng.RandomStream of the inner.
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 \(S(t_0) = \mathtt{s0}\).
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 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.
void	resetStartProcess ()
	Resets the observation counter to its initial value \(j=0\), so that the current observation \(X(t_j)\) becomes \(X(t_0)\).
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

Same as GammaProcessPCA, but the generated uniforms correspond to a bridge transformation of the BrownianMotionPCA instead of a sequential transformation.

Definition at line 38 of file GammaProcessPCABridge.java.

Constructor & Destructor Documentation

◆ GammaProcessPCABridge()

umontreal.ssj.stochprocess.GammaProcessPCABridge.GammaProcessPCABridge	(	double	s0,
		double	mu,
		double	nu,
		RandomStream	stream )

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

The same stream is used to generate the gamma and beta random numbers. All these numbers are generated by inversion in the following order: the first uniform random number generated is used for the gamma and the other \(d-1\) for the beta’s.

Definition at line 53 of file GammaProcessPCABridge.java.

Member Function Documentation

◆ generatePath() [1/2]

double[] umontreal.ssj.stochprocess.GammaProcessPCABridge.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.GammaProcessPCA.

Reimplemented in umontreal.ssj.stochprocess.GammaProcessPCASymmetricalBridge.

Definition at line 99 of file GammaProcessPCABridge.java.

◆ generatePath() [2/2]

double[] umontreal.ssj.stochprocess.GammaProcessPCABridge.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.GammaProcessPCA.

Reimplemented in umontreal.ssj.stochprocess.GammaProcessPCASymmetricalBridge.

Definition at line 58 of file GammaProcessPCABridge.java.