## Class VARIMAModel

• Direct Known Subclasses:
VARMAModel

public class VARIMAModel
extends VARIMAXModel
An ARIMA(p, d, q) process, Yt, is such that $X_t = (1 - L)^d Y_t$ where L is the lag operator, d the order of difference, Xt an ARMA(p, q) process, for which $X_t = \mu + \Sigma \phi_i X_{t-i} + \Sigma \theta_j \epsilon_{t-j} + \epsilon_t,$ Xt, μ and εt are n-dimensional vectors. The (n * n) matrices $${\phi_i}$$ and $${\theta_j}$$ are the AR and MA coefficients respectively.
See Also:
Wikipedia: Autoregressive integrated moving average
• ### Constructor Summary

Constructors
Constructor Description
VARIMAModel​(Matrix[] phi, int d, Matrix[] theta)
Construct a multivariate ARIMA model with unit variance and zero-intercept (mu).
VARIMAModel​(Matrix[] phi, int d, Matrix[] theta, Matrix sigma)
Construct a multivariate ARIMA model with zero-intercept (mu).
VARIMAModel​(Vector mu, Matrix[] phi, int d, Matrix[] theta)
Construct a multivariate ARIMA model with unit variance.
VARIMAModel​(Vector mu, Matrix[] phi, int d, Matrix[] theta, Matrix sigma)
Construct a multivariate ARIMA model.
VARIMAModel​(VARIMAModel that)
Copy constructor.
VARIMAModel​(ARIMAModel model)
Construct a multivariate model from a univariate ARIMA model.
• ### Method Summary

All Methods
Modifier and Type Method Description
VARMAModel getVARMA()
Get the ARMA part of this ARIMA model, essentially ignoring the differencing.
• ### Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel

AR, d, dimension, getVARMAX, MA, maxPQ, mu, p, phi, psi, q, sigma, theta
• ### Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
• ### Constructor Detail

• #### VARIMAModel

public VARIMAModel​(Vector mu,
Matrix[] phi,
int d,
Matrix[] theta,
Matrix sigma)
Construct a multivariate ARIMA model.
Parameters:
mu - the intercept (constant) vector
phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
d - the order of integration
theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
sigma - the white noise covariance matrix
• #### VARIMAModel

public VARIMAModel​(Vector mu,
Matrix[] phi,
int d,
Matrix[] theta)
Construct a multivariate ARIMA model with unit variance.
Parameters:
mu - the intercept (constant) vector
phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
d - the order of integration
theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
• #### VARIMAModel

public VARIMAModel​(Matrix[] phi,
int d,
Matrix[] theta,
Matrix sigma)
Construct a multivariate ARIMA model with zero-intercept (mu).
Parameters:
phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
d - the order of integration
theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
sigma - the white noise covariance matrix
• #### VARIMAModel

public VARIMAModel​(Matrix[] phi,
int d,
Matrix[] theta)
Construct a multivariate ARIMA model with unit variance and zero-intercept (mu).
Parameters:
phi - the AR coefficients (excluding the initial 1); null if no AR coefficient
d - the order of integration
theta - the MA coefficients (excluding the initial 1); null if no MA coefficient
• #### VARIMAModel

public VARIMAModel​(ARIMAModel model)
Construct a multivariate model from a univariate ARIMA model.
Parameters:
model - a univariate ARIMA model
• #### VARIMAModel

public VARIMAModel​(VARIMAModel that)
Copy constructor.
Parameters:
that - a multivariate ARIMA model
• ### Method Detail

• #### getVARMA

public VARMAModel getVARMA()
Get the ARMA part of this ARIMA model, essentially ignoring the differencing.
Returns:
the ARMA part