SSJ
V. labo.

umontreal.iro.lecuyer.stochprocess
Class MultivariateBrownianMotionBridge

java.lang.Object
  extended by umontreal.iro.lecuyer.stochprocess.StochasticProcess
      extended by umontreal.iro.lecuyer.stochprocess.MultivariateStochasticProcess
          extended by umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotion
              extended by umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotionBridge

public class MultivariateBrownianMotionBridge
extends MultivariateBrownianMotion

A multivariate Brownian motion process {X(t) : t >= 0} sampled via bridge sampling. We use a Cholesky decomposition of the relevant covariance matrix to generate the next c-dimensional vector at each step of the bridge sampling algorithm. For this, we construct the same matrix Σ as in MultivariateBrownianMotion and we compute its Cholesky decomposition Σ = BBt.


Constructor Summary
MultivariateBrownianMotionBridge(int c, double[] x0, double[] mu, double[] sigma, double[][] corrZ, NormalGen gen)
          Constructs a new MultivariateBrownianMotionBridge with parameters μ =mu, σ =sigma, correlation matrix Rz =corrZ, and initial value X(t0) =x0.
MultivariateBrownianMotionBridge(int c, double[] x0, double[] mu, double[] sigma, double[][] corrZ, RandomStream stream)
          Constructs a new MultivariateBrownianMotionBridge with parameters μ =mu, σ =sigma, correlation matrix Rz =corrZ, and initial value X(t0) =x0.
 
Method Summary
 double[] generatePath()
          .
 double[] nextObservationVector()
          Generates and returns the next observation X(tj) of the multivariate stochastic process in a vector created automatically.
 void nextObservationVector(double[] obs)
          Generates and returns in obs the next observation X(tj) of the multivariate stochastic process.
 void resetStartProcess()
          Resets the observation counter to its initial value j = 0, so that the current observation X(tj) becomes X(t0).
 
Methods inherited from class umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotion
generatePath, generatePath, getGen, getMu, getStream, nextObservationVector, nextObservationVector, setParams, setParams, setStream
 
Methods inherited from class umontreal.iro.lecuyer.stochprocess.MultivariateStochasticProcess
getCurrentObservation, getDimension, getObservation, getObservation, getSubpath, getX0, setObservationTimes
 
Methods inherited from class umontreal.iro.lecuyer.stochprocess.StochasticProcess
getArrayMappingCounterToIndex, getCurrentObservation, getCurrentObservationIndex, getNbObservationTimes, getObservation, getObservationTimes, getPath, getX0, hasNextObservation, nextObservation, setObservationTimes, setX0
 
Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

MultivariateBrownianMotionBridge

public MultivariateBrownianMotionBridge(int c,
                                        double[] x0,
                                        double[] mu,
                                        double[] sigma,
                                        double[][] corrZ,
                                        RandomStream stream)
Constructs a new MultivariateBrownianMotionBridge with parameters μ =mu, σ =sigma, correlation matrix Rz =corrZ, and initial value X(t0) =x0. The normal variates Zj in are generated by inversion using the RandomStream stream.


MultivariateBrownianMotionBridge

public MultivariateBrownianMotionBridge(int c,
                                        double[] x0,
                                        double[] mu,
                                        double[] sigma,
                                        double[][] corrZ,
                                        NormalGen gen)
Constructs a new MultivariateBrownianMotionBridge with parameters μ =mu, σ =sigma, correlation matrix Rz =corrZ, and initial value X(t0) =x0. The normal variates Zj in are generated by gen.

Method Detail

generatePath

public double[] generatePath()
Description copied from class: MultivariateStochasticProcess
. \begin{tabb}Generates, returns, and saves the sample path
 $\{\bX(t_{0}), \bX(t_{...
 ...cj + i-1]}
 contains $X_i(t_j)$\ for $j=0,\dots,d$\ and $i=1,\dots,c$.
 \end{tabb}

Overrides:
generatePath in class MultivariateBrownianMotion

resetStartProcess

public void resetStartProcess()
Description copied from class: StochasticProcess
Resets the observation counter to its initial value j = 0, so that the current observation X(tj) becomes X(t0). This method should be invoked before generating observations sequentially one by one via nextObservation, for a new sample path.

Overrides:
resetStartProcess in class StochasticProcess

nextObservationVector

public double[] nextObservationVector()
Description copied from class: MultivariateBrownianMotion
Generates and returns the next observation X(tj) of the multivariate stochastic process in a vector created automatically. The processe is sampled sequentially, i.e. if the last observation generated was for time tj-1, the next observation returned will be for time tj.

Overrides:
nextObservationVector in class MultivariateBrownianMotion

nextObservationVector

public void nextObservationVector(double[] obs)
Description copied from class: MultivariateBrownianMotion
Generates and returns in obs the next observation X(tj) of the multivariate stochastic process. The processe is sampled sequentially, i.e. if the last observation generated was for time tj-1, the next observation returned will be for time tj.

Overrides:
nextObservationVector in class MultivariateBrownianMotion

SSJ
V. labo.

To submit a bug or ask questions, send an e-mail to Pierre L'Ecuyer.