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

public class ARMAXModel
extends ARIMAXModel

The ARMAX model (ARIMA model with eXogenous inputs) is a generalization of the ARMA model by incorporating exogenous variables. X_t is an ARMAX(p, q) process, for which \[ X_t = \mu + \sum_{i=1}^p \phi_i X_{t-i} + \sum_{i=1}^q \theta_j \epsilon_{t-j} + \psi' D_t + \epsilon_t, \] where D_t is an (m * 1) vector which contains all exogenous variables at time t (excluding 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)

Constructor Summary

ARMAXModel(ARMAXModel that)
Copy constructor.

ARMAXModel(double[] AR, double[] MA, double[] psi)
Construct a univariate ARMAX model with unit variance and zero-intercept (mu).

ARMAXModel(double[] AR, double[] MA, double[] psi, double sigma)
Construct a univariate ARMAX model with zero-intercept (mu).

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 model.

Method Summary

double

armaxMean(double[] arLags, double[] maLags, double[] exVar) Compute the univariate ARMAX conditional mean.

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

AR, d, getARMAX, MA, maxPQ, mu, p, phi, phiPolynomial, psi, q, sigma, theta, thetaPolynomial, 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 model.

Parameters:

mu - the intercept (constant) term

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

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

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 coefficients

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

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

ARMAXModel

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

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

Parameters:

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

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

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

Parameters:

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

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

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

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