Class MultivariateFt
- java.lang.Object
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- dev.nm.stat.stochasticprocess.multivariate.sde.MultivariateFt
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- All Implemented Interfaces:
DeepCopyable
- Direct Known Subclasses:
MultivariateFtWt
public class MultivariateFt extends Object implements DeepCopyable
This represents the concept 'Filtration', the information available at time t. The information may include (subject to implementation), for example,- time
- value of the stochastic process
- values of the driving Brownian motion(s)
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Constructor Summary
Constructors Constructor Description MultivariateFt()Construct an empty filtration (no information).MultivariateFt(MultivariateFt that)Copy constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description MultivariateFtdeepCopy()The implementation returns an instance created fromthisby the copy constructor of the class, or justthisif the instance itself is immutable.intdim()Get the dimension of the process.doubledt()Get the current time differential.VectordWt()Get the increment of the driving Brownian motion during the time differential.intnB()Get the number of independent driving Brownian motions.voidsetDt(double dt)Set the current time differential.voidsetXt(Vector Xt)Set the current value of the stochastic process.voidsetZt(Vector Zt)Set the current value of the Gaussian innovation.VectorXt()Get the current value of the stochastic process.VectorZt()Get the current value of the Gaussian innovation.
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Constructor Detail
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MultivariateFt
public MultivariateFt()
Construct an empty filtration (no information).
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MultivariateFt
public MultivariateFt(MultivariateFt that)
Copy constructor.- Parameters:
that- anotherFt
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Method Detail
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deepCopy
public MultivariateFt deepCopy()
Description copied from interface:DeepCopyableThe implementation returns an instance created fromthisby the copy constructor of the class, or justthisif the instance itself is immutable.- Specified by:
deepCopyin interfaceDeepCopyable- Returns:
- an independent (deep) copy of the instance
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dim
public int dim()
Get the dimension of the process.- Returns:
- the dimension of the process
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nB
public int nB()
Get the number of independent driving Brownian motions.- Returns:
- the number of independent driving Brownian motions
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setDt
public void setDt(double dt)
Set the current time differential.- Parameters:
dt- the time differential
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dt
public double dt()
Get the current time differential.- Returns:
- the time differential
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setXt
public void setXt(Vector Xt)
Set the current value of the stochastic process.- Parameters:
Xt- the current value of the stochastic process
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Xt
public Vector Xt()
Get the current value of the stochastic process.- Returns:
- the current value of the stochastic process
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setZt
public void setZt(Vector Zt)
Set the current value of the Gaussian innovation.- Parameters:
Zt- the current Gaussian innovation
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Zt
public Vector Zt()
Get the current value of the Gaussian innovation.- Returns:
- the current Gaussian innovation
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dWt
public Vector dWt()
Get the increment of the driving Brownian motion during the time differential. This is the product of the Gaussian innovation and the square root of the time differential.- Returns:
- the increment of the driving Brownian motion during the time differential
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