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 ImmutableMatrixC0()Get the covariance matrix of x0.intgetObsDimension()Get the dimension of the observations.MultivariateObservationEquationgetObservationModel()Get the observation model.intgetStateDimension()Get the dimension of states.MultivariateStateEquationgetStateModel()Get the state model.ImmutableVectorm0()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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