Package dev.nm.stat.dlm.multivariate
Class MultivariateDLMSim
- java.lang.Object
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- dev.nm.stat.dlm.multivariate.MultivariateDLMSim
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public class MultivariateDLMSim extends Object
This is a simulator for a multivariate controlled dynamic linear model process. For (t ≥ 1), a controlled DLM takes the following form: Observation Equation:yt = Ft * xt + vt,
State Equation:xt = Gt * xt-1 + Ht * ut + wt,
Given the model parameters, the time series of control variables {ut} and an integer (length) T, This simulator generates both the states {xt} and observations {yt}.
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Nested Class Summary
Nested Classes Modifier and Type Class Description static class
MultivariateDLMSim.Innovation
a simulated innovation
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Constructor Summary
Constructors Constructor Description MultivariateDLMSim(MultivariateDLM model, NormalRVG rmvnorm)
Simulates a multivariate controlled dynamic linear model process.
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Method Summary
All Methods Instance Methods Concrete Methods Modifier and Type Method Description MultivariateDLMSim.Innovation
next(Vector u)
Gets the next innovation.
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Constructor Detail
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MultivariateDLMSim
public MultivariateDLMSim(MultivariateDLM model, NormalRVG rmvnorm)
Simulates a multivariate controlled dynamic linear model process.- Parameters:
model
- a multivariate controlled dynamic linear modelrmvnorm
- a standard multivariate Gaussian random vector generator (for seeding)
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Method Detail
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next
public MultivariateDLMSim.Innovation next(Vector u)
Gets the next innovation.- Parameters:
u
- the control vector as of time t - 1; used not for the first innovation (initial state)- Returns:
- a simulated innovation
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