com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arma

Class ARMAXModel

java.lang.Object

com.numericalmethod.suanshu.stats.timeseries.linear.univariate.arima.ARIMAXModel

com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arma.ARMAXModel

All Implemented Interfaces:

java.io.Serializable

public class ARMAXModel
extends ARIMAXModel

This class represents a univariate ARMAX (ARMA model with eXogenous inputs) model.

The ARMAX model incorporates exogenous variables and it can be considered as a generalization of the ARMA model. Let Y_t be an ARMAX process, then

Y_t = μ + Σ φ_i * Y_{t-i} + Σ θ_j * ε_{t-j} + ψ * D_t + ε_t,

where D_t is an (m * 1) vector which contains all exogenous variables at time t (excl. the intercept term), and its coefficients are represented by an m-dimensional vector ψ.

See Also:

Wikipedia: Autoregressive moving average model with exogenous inputs model (ARMAX model), Serialized Form

Field Summary

Fields inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.arima.ARIMAXModel

AR, MA, mu, psi, sigma

Constructor Summary

Constructors

Constructor and Description
ARMAXModel(ARMAXModel that) Copy constructor.
ARMAXModel(double[] AR, double[] MA, double[] psi) Construct a zero-intercept (mu) univariate ARMAX model with unit variance.
ARMAXModel(double[] AR, double[] MA, double[] psi, double sigma) Construct a zero-intercept (mu) univariate ARMAX model.
ARMAXModel(double mu, double[] AR, double[] MA, double[] psi) Construct a univariate ARMAX model with unit variance.
ARMAXModel(double mu, double[] AR, double[] MA, double[] psi, double sigma) Construct a univariate ARMAX (ARMA model with eXogenous inputs) model.

Method Summary

Modifier and Type	Method and Description
double	armaxMean(double[] arLags, double[] maLags, double[] exVar) Compute the univariate ARMAX conditional mean.
double	armaxMeanNoIntercept(double[] arLags, double[] maLags, double[] exVar) Compute the zero-intercept (mu) univariate ARMAX conditional mean.

Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.arima.ARIMAXModel

AR, AR, d, getArmax, MA, MA, maxPQ, mu, p, psi, q, sigma, toString

Methods inherited from class java.lang.Object

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

Constructor Detail

ARMAXModel

public ARMAXModel(double mu,
                  double[] AR,
                  double[] MA,
                  double[] psi,
                  double sigma)

Construct a univariate ARMAX (ARMA model with eXogenous inputs) model.

Parameters:

mu - the intercept (constant) term

AR - the AR coefficients (excluding the initial 1); null if no AR coefficient

MA - the MA coefficients (excluding the initial 1); null if no MA coefficient

psi - the coefficients of the deterministic terms (excluding the intercept term)

sigma - the white noise variance

ARMAXModel

public ARMAXModel(double mu,
                  double[] AR,
                  double[] MA,
                  double[] psi)

Construct a univariate ARMAX model with unit variance.

Parameters:

mu - the intercept (constant) term

AR - the AR coefficients (excluding the initial 1); null if no AR coefficient

MA - the MA coefficients (excluding the initial 1); null if no MA coefficient

psi - the coefficients of the deterministic terms (excluding the intercept term)

ARMAXModel

public ARMAXModel(double[] AR,
                  double[] MA,
                  double[] psi,
                  double sigma)

Construct a zero-intercept (mu) univariate ARMAX model.

Parameters:

AR - the AR coefficients (excluding the initial 1); null if no AR coefficient

MA - the MA coefficients (excluding the initial 1); null if no MA coefficient

psi - the coefficients of the deterministic terms (excluding the intercept term)

sigma - the white noise variance

ARMAXModel

public ARMAXModel(double[] AR,
                  double[] MA,
                  double[] psi)

Construct a zero-intercept (mu) univariate ARMAX model with unit variance.

Parameters:

AR - the AR coefficients (excluding the initial 1); null if no AR coefficient

MA - the MA coefficients (excluding the initial 1); null if no MA coefficient

psi - the coefficients of the deterministic terms (excluding the intercept term)

ARMAXModel

public ARMAXModel(ARMAXModel that)

Copy constructor.

Parameters:

that - a univariate ARMAX model

Method Detail

armaxMeanNoIntercept

public double armaxMeanNoIntercept(double[] arLags,
                                   double[] maLags,
                                   double[] exVar)

Compute the zero-intercept (mu) univariate ARMAX conditional mean.

Parameters:

arLags - the AR lags

maLags - the MA lags

exVar - the exogenous variables

Returns:

the conditional mean

armaxMean

public double armaxMean(double[] arLags,
                        double[] maLags,
                        double[] exVar)

Compute the univariate ARMAX conditional mean.

Parameters:

arLags - the AR lags

maLags - the MA lags

exVar - the exogenous variables

Returns:

the conditional mean