dev.nm.stat.dlm.multivariate

Class MultivariateDLMSeries

java.lang.Object

dev.nm.stat.dlm.multivariate.MultivariateDLMSeries

All Implemented Interfaces:

TimeSeries<Integer,MultivariateDLMSim.Innovation,MultivariateDLMSeries.Entry>, Iterable<MultivariateDLMSeries.Entry>

public class MultivariateDLMSeries
extends Object
implements TimeSeries<Integer,MultivariateDLMSim.Innovation,MultivariateDLMSeries.Entry>

This is a simulator for a multivariate 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}.

This implementation is appropriate for a short time series when the size is known; otherwise use instead DLMSim.

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	MultivariateDLMSeries.Entry This is the TimeSeries.Entry for a multivariate DLM time series.

Constructor Summary

Constructors

Constructor and Description
MultivariateDLMSeries(int T, MultivariateDLM model) Simulate a multivariate controlled dynamic linear model process.
MultivariateDLMSeries(int T, MultivariateDLM model, MultivariateIntTimeTimeSeries Ut) Simulate a multivariate controlled dynamic linear model process.
MultivariateDLMSeries(int T, MultivariateDLM model, MultivariateIntTimeTimeSeries Ut, NormalRVG rmvnorm) Simulate a multivariate controlled dynamic linear model process.

Method Summary

Modifier and Type	Method and Description
MultivariateSimpleTimeSeries	getObservations() Get the observations.
MultivariateSimpleTimeSeries	getStates() Get the states.
Iterator<MultivariateDLMSeries.Entry>	iterator()
int	size() Get the length of the time series.

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.lang.Iterable

forEach, spliterator

Constructor Detail

MultivariateDLMSeries

public MultivariateDLMSeries(int T,
                             MultivariateDLM model,
                             MultivariateIntTimeTimeSeries Ut,
                             NormalRVG rmvnorm)

Simulate a multivariate controlled dynamic linear model process.

Parameters:

T - the length of the multivariate time series (states and observations) to generate

model - a multivariate controlled dynamic linear model

Ut - an m-dimensional time series of control variables (length = T); use null if no control

rmvnorm - a standard multivariate Gaussian random vector generator (for seeding)

MultivariateDLMSeries

public MultivariateDLMSeries(int T,
                             MultivariateDLM model,
                             MultivariateIntTimeTimeSeries Ut)

Simulate a multivariate controlled dynamic linear model process.

Parameters:

T - the length of the multivariate time series (states and observations) to generate

model - a multivariate controlled dynamic linear model

Ut - an m-dimensional time series of control variables (length = T); use null if no control

MultivariateDLMSeries

public MultivariateDLMSeries(int T,
                             MultivariateDLM model)

Simulate a multivariate controlled dynamic linear model process.

Parameters:

T - the length of the multivariate time series (states and observations) to generate

model - a multivariate controlled dynamic linear model

Method Detail

size

public int size()

Description copied from interface: TimeSeries

Get the length of the time series.

Specified by:

size in interface TimeSeries<Integer,MultivariateDLMSim.Innovation,MultivariateDLMSeries.Entry>

Returns:

the time series length

iterator

public Iterator<MultivariateDLMSeries.Entry> iterator()

Specified by:

iterator in interface Iterable<MultivariateDLMSeries.Entry>

getStates

public MultivariateSimpleTimeSeries getStates()

Get the states.

Returns:

the simulated states

getObservations

public MultivariateSimpleTimeSeries getObservations()

Get the observations.

Returns:

the simulated observations