dev.nm.stat.dlm.univariate

Class DLMSim

java.lang.Object

dev.nm.stat.dlm.univariate.DLMSim

public class DLMSim
extends Object

This is a simulator for a univariate controlled dynamic linear model process. For (t ≥ 1), a controlled DLM takes the following form:

Observation Equation: \[ y_{t} = F_{t} \cdot x_{t} + v_{t}, \] State Equation: \[ x_{t} = G_{t} \cdot x_{t-1} + H_{t} \cdot u_{t} + w_{t}, \] Given the model parameters, the time series of control variables {u_t} and an integer (length) T, This simulator generates both the states {x_t} and observations {y_t}.

See Also:

"G. Petris et al., "ch. 2, pp. 31-84," Dynamic Linear Models with R, New York, Springer, 2009."

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DLMSim.Innovation a simulated innovation

Constructor Summary

Constructors

Constructor and Description
DLMSim(DLM model, RandomStandardNormalGenerator rnorm) Simulate a univariate controlled dynamic linear model process.

Method Summary

Modifier and Type	Method and Description
DLMSim.Innovation	next(double u) Get the next innovation.

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Constructor Detail

DLMSim

public DLMSim(DLM model,
              RandomStandardNormalGenerator rnorm)

Simulate a univariate controlled dynamic linear model process.

Parameters:

model - a univariate controlled dynamic linear model

rnorm - a standard Gaussian random number generator (for seeding)

Method Detail

next

public DLMSim.Innovation next(double u)

Get the next innovation.

Parameters:

u - the control as of time t - 1; used not for the first innovation (initial state)

Returns:

a simulated innovation