# SuanShu, a Java numerical and statistical library

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

## Class ARIMAModel

• Direct Known Subclasses:
ARMAModel

public class ARIMAModel
extends ARIMAXModel
An ARIMA(p, d, q) process, Xt, is such that $(1 - B)^d X_t = Y_t$ where B is the backward or lag operator, d the order of difference, Yt an ARMA(p, q) process, for which $Y_t = \mu + \Sigma \phi_i Y_{t-i} + \Sigma \theta_j \epsilon_{t-j} + \epsilon_t,$
Wikipedia: Autoregressive integrated moving average
• ### Constructor Summary

Constructors
Constructor and Description
ARIMAModel(ARIMAModel that)
Copy constructor.
ARIMAModel(double[] AR, int d, double[] MA)
Construct a univariate ARIMA model with unit variance and zero-intercept (mu).
ARIMAModel(double[] AR, int d, double[] MA, double sigma)
Construct a univariate ARIMA model with zero-intercept (mu).
ARIMAModel(double mu, double[] AR, int d, double[] MA)
Construct a univariate ARIMA model with unit variance.
ARIMAModel(double mu, double[] AR, int d, double[] MA, double sigma)
Construct a univariate ARIMA model.
• ### Method Summary

All Methods
Modifier and Type Method and Description
ARMAModel getARMA()
Get the ARMA part of this ARIMA model, essentially ignoring the differencing.
• ### 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

• #### ARIMAModel

public ARIMAModel(double mu,
double[] AR,
int d,
double[] MA,
double sigma)
Construct a univariate ARIMA model.
Parameters:
mu - the intercept (constant) term
AR - the AR coefficients (excluding the initial 1); null if no AR coefficients
d - the order of integration
MA - the MA coefficients (excluding the initial 1); null if no MA coefficients
sigma - the white noise variance
• #### ARIMAModel

public ARIMAModel(double mu,
double[] AR,
int d,
double[] MA)
Construct a univariate ARIMA model with unit variance.
Parameters:
mu - the intercept (constant) term
AR - the AR coefficients (excluding the initial 1); null if no AR coefficients
d - the order of integration
MA - the MA coefficients (excluding the initial 1); null if no MA coefficients
• #### ARIMAModel

public ARIMAModel(double[] AR,
int d,
double[] MA,
double sigma)
Construct a univariate ARIMA model with zero-intercept (mu).
Parameters:
AR - the AR coefficients (excluding the initial 1); null if no AR coefficients
d - the order of integration
MA - the MA coefficients (excluding the initial 1); null if no MA coefficients
sigma - the white noise variance
• #### ARIMAModel

public ARIMAModel(double[] AR,
int d,
double[] MA)
Construct a univariate ARIMA model with unit variance and zero-intercept (mu).
Parameters:
AR - the AR coefficients (excluding the initial 1); null if no AR coefficients
d - the order of integration
MA - the MA coefficients (excluding the initial 1); null if no MA coefficients
• #### ARIMAModel

public ARIMAModel(ARIMAModel that)
Copy constructor.
Parameters:
that - a univariate ARIMA model
• ### Method Detail

• #### getARMA

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