|
SSJ V. labo. |
||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |
java.lang.Objectumontreal.iro.lecuyer.stochprocess.StochasticProcess
umontreal.iro.lecuyer.stochprocess.MultivariateStochasticProcess
umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotion
umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotionPCABigSigma
public class MultivariateBrownianMotionPCABigSigma
A multivariate Brownian motion process
{X(t) : t >= 0} sampled entirely using the
principal component decomposition (PCA). In this class, a matrix which
equals the Kronecker products of two matrices C and Σ must be computed.
C is the usual one dimensional Brownian motion covariance matrix
and Σ is the matrix that defined the covariance between the
one dimensionnal Brownian motion. This Kronecker products is time and
memory consuming as it might creates an enormous matrix, matrix that is called
BigSigma here. The class MultivariateBrownianMotionPCA
provides
faster results.
Constructor Summary | |
---|---|
MultivariateBrownianMotionPCABigSigma(int c,
double[] x0,
double[] mu,
double[] sigma,
double[][] corrZ,
NormalGen gen)
Constructs a new MultivariateBrownianMotionPCABigSigma with parameters μ = |
|
MultivariateBrownianMotionPCABigSigma(int c,
double[] x0,
double[] mu,
double[] sigma,
double[][] corrZ,
RandomStream stream)
Constructs a new MultivariateBrownianMotionPCABigSigma with parameters μ = |
Method Summary | |
---|---|
double[] |
generatePath()
Generates, returns, and saves the sample path {X(t0),X(t1),…,X(td)}, which can then be accessed via getPath, getSubpath, or getObservation. |
double[] |
generatePath(double[] uniform01)
Same as generatePath() but requires a vector of uniform random numbers which are used to generate the path. |
void |
setParams(int c,
double[] x0,
double[] mu,
double[] sigma,
double[][] corrZ)
Sets the dimension c = |
Methods inherited from class umontreal.iro.lecuyer.stochprocess.MultivariateBrownianMotion |
---|
generatePath, getGen, getMu, getStream, nextObservationVector, nextObservationVector, nextObservationVector, nextObservationVector, 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, resetStartProcess, setObservationTimes, setX0 |
Methods inherited from class java.lang.Object |
---|
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
---|
public MultivariateBrownianMotionPCABigSigma(int c, double[] x0, double[] mu, double[] sigma, double[][] corrZ, RandomStream stream)
RandomStream
stream.
public MultivariateBrownianMotionPCABigSigma(int c, double[] x0, double[] mu, double[] sigma, double[][] corrZ, NormalGen gen)
Method Detail |
---|
public void setParams(int c, double[] x0, double[] mu, double[] sigma, double[][] corrZ)
MultivariateBrownianMotion
setParams
in class MultivariateBrownianMotion
public double[] generatePath()
MultivariateStochasticProcess
generatePath
in class MultivariateBrownianMotion
public double[] generatePath(double[] uniform01)
MultivariateBrownianMotion
generatePath
in class MultivariateBrownianMotion
|
SSJ V. labo. |
||||||||
PREV CLASS NEXT CLASS | FRAMES NO FRAMES | ||||||||
SUMMARY: NESTED | FIELD | CONSTR | METHOD | DETAIL: FIELD | CONSTR | METHOD |