Package dev.nm.stat.dlm.multivariate
Class MultivariateDLM
- java.lang.Object
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- dev.nm.stat.dlm.multivariate.MultivariateDLM
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public class MultivariateDLM extends Object
This is the multivariate controlled DLM (controlled Dynamic Linear Model) specification. A controlled DLM, for (t ≥ 1), is described by two equations: the observation and state equations. Observation Equation:yt = Ft * xt + vt,
State Equation:xt = Gt * xt-1 + Ht * ut + wt,
{yt} are the observation vectors; {xt} are the state vectors. Ft and Gt are known matrices of dimension (number of observations * number of states) and (number of states * number of states) respectively. {vt} and {wt} are two independent sequences of independent normal random vectors with mean zero and known variance matrices {Vt} and {Wt}, respectively; Furthermore, it is assumed that x0 is independent of {vt} and {wt} and is normally distributed with mean m0 and covariance matrix C0, where m0 is a vector of length the same as the number of states and C0 is a matrix of dimension (number of states * number of states); ut is an m-dimensional vector of control variables, i.e., the variables whose values can be regulated by the user, in order to obtain a desired level of the state xt. Ht is a known matrix of coefficients, with dimension of (number of states * m).- See Also:
- G. Petris et al., "ch. 2, pp. 31-84," Dynamic Linear Models with R, New York, Springer, 2009.
- Wikipedia: Kalman filter - Underlying dynamic system model
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Constructor Summary
Constructors Constructor Description MultivariateDLM(Vector m0, Matrix C0, MultivariateObservationEquation Yt, MultivariateStateEquation Xt)
Construct a (multivariate) controlled dynamic linear model.MultivariateDLM(MultivariateDLM that)
Copy constructor.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description ImmutableMatrix
C0()
Get the covariance matrix of x0.int
getObsDimension()
Get the dimension of the observations.MultivariateObservationEquation
getObservationModel()
Get the observation model.int
getStateDimension()
Get the dimension of states.MultivariateStateEquation
getStateModel()
Get the state model.ImmutableVector
m0()
Get the the mean of x0.
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Constructor Detail
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MultivariateDLM
public MultivariateDLM(Vector m0, Matrix C0, MultivariateObservationEquation Yt, MultivariateStateEquation Xt)
Construct a (multivariate) controlled dynamic linear model.- Parameters:
m0
- the mean of x0C0
- the covariance matrix of x0Yt
- the observation equation for the modelXt
- the state equation for the model
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MultivariateDLM
public MultivariateDLM(MultivariateDLM that)
Copy constructor.- Parameters:
that
- a (multivariate) controlled dynamic linear model
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Method Detail
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m0
public ImmutableVector m0()
Get the the mean of x0.- Returns:
- m0, the mean of x0
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C0
public ImmutableMatrix C0()
Get the covariance matrix of x0.- Returns:
- C0, the covariance matrix of x0
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getObsDimension
public int getObsDimension()
Get the dimension of the observations.- Returns:
- the dimension of the observations
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getStateDimension
public int getStateDimension()
Get the dimension of states.- Returns:
- the dimension of states
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getObservationModel
public MultivariateObservationEquation getObservationModel()
Get the observation model.- Returns:
- the observation model
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getStateModel
public MultivariateStateEquation getStateModel()
Get the state model.- Returns:
- the state model
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