com.numericalmethod.suanshu.stats.dlm.multivariate

Class DLMSeries

java.lang.Object

com.numericalmethod.suanshu.stats.dlm.multivariate.DLMSeries

All Implemented Interfaces:

TimeSeries<java.lang.Integer,DLMSim.Innovation,DLMSeries.Entry>, java.io.Serializable, java.lang.Iterable<DLMSeries.Entry>

public class DLMSeries
extends java.lang.Object
implements TimeSeries<java.lang.Integer,DLMSim.Innovation,DLMSeries.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 * x_t + v_t,

State Equation:

x_t = G_t * x_t-1 + H_t * 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., "Dynamic Linear Models with R," New York, Springer, 2009, ch. 2, pp. 31-84.", Serialized Form

Nested Class Summary

Nested Classes

Modifier and Type	Class and Description
static class	DLMSeries.Entry This is the TimeSeries.Entry for a multivariate DLM time series.

Constructor Summary

Constructors

Constructor and Description
DLMSeries(int T, DLM model) Simulate a multivariate controlled dynamic linear model process.
DLMSeries(int T, DLM model, MultiVariateTimeSeries Ut) Simulate a multivariate controlled dynamic linear model process.
DLMSeries(int T, DLM model, MultiVariateTimeSeries Ut, NormalRvg rmvnorm) Simulate a multivariate controlled dynamic linear model process.

Method Summary

Modifier and Type	Method and Description
SimpleMultiVariateTimeSeries	getObservations() Get the observations.
SimpleMultiVariateTimeSeries	getStates() Get the states.
java.util.Iterator<DLMSeries.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

DLMSeries

public DLMSeries(int T,
                 DLM model,
                 MultiVariateTimeSeries 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)

DLMSeries

public DLMSeries(int T,
                 DLM model,
                 MultiVariateTimeSeries 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

DLMSeries

public DLMSeries(int T,
                 DLM 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<java.lang.Integer,DLMSim.Innovation,DLMSeries.Entry>

Returns:

the time series length

iterator

public java.util.Iterator<DLMSeries.Entry> iterator()

Specified by:

iterator in interface java.lang.Iterable<DLMSeries.Entry>

getStates

public SimpleMultiVariateTimeSeries getStates()

Get the states.

Returns:

the simulated states

getObservations

public SimpleMultiVariateTimeSeries getObservations()

Get the observations.

Returns:

the simulated observations