SuanShu, a Java numerical and statistical library

com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.arma
Class ArmaModel

java.lang.Object
  extended by com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaxModel
      extended by com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaModel
          extended by com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.arma.ArmaModel
Direct Known Subclasses:
ArModel, MaModel

public class ArmaModel
extends ArimaModel

This class represents a univariate ARMA model.

See Also:
Wikipedia: Autoregressive moving average model

Field Summary
 
Fields inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaxModel
AR, MA, mu, psi, sigma
 
Constructor Summary
ArmaModel(ArmaModel that)
          Copy constructor.
ArmaModel(double[] AR, double[] MA)
          Construct a zero-intercept (mu) univariate ARMA model with unit variance.
ArmaModel(double[] AR, double[] MA, double sigma)
          Construct a zero-intercept (mu) univariate ARMA model.
ArmaModel(double mu, double[] AR, double[] MA)
          Construct a univariate ARMA model with unit variance.
ArmaModel(double mu, double[] AR, double[] MA, double sigma)
          Construct a univariate ARMA model.
 
Method Summary
 double armaMean(double[] arLags, double[] maLags)
          Compute the univariate ARMA conditional mean.
 double armaMeanNoIntercept(double[] arLags, double[] maLags)
          Compute the zero-intercept (mu) univariate ARMA conditional mean.
 
Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaModel
getArma
 
Methods inherited from class com.numericalmethod.suanshu.stats.timeseries.linear.univariate.stationaryprocess.arima.ArimaxModel
AR, AR, d, getArmax, MA, MA, maxPQ, mu, p, psi, q, sigma
 
Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait
 

Constructor Detail

ArmaModel

public ArmaModel(double mu,
                 double[] AR,
                 double[] MA,
                 double sigma)
Construct a univariate ARMA 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
sigma - the white noise variance

ArmaModel

public ArmaModel(double mu,
                 double[] AR,
                 double[] MA)
Construct a univariate ARMA 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

ArmaModel

public ArmaModel(double[] AR,
                 double[] MA,
                 double sigma)
Construct a zero-intercept (mu) univariate ARMA 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
sigma - the white noise variance

ArmaModel

public ArmaModel(double[] AR,
                 double[] MA)
Construct a zero-intercept (mu) univariate ARMA 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

ArmaModel

public ArmaModel(ArmaModel that)
Copy constructor.

Parameters:
that - a univariate ARMA model
Method Detail

armaMeanNoIntercept

public double armaMeanNoIntercept(double[] arLags,
                                  double[] maLags)
Compute the zero-intercept (mu) univariate ARMA conditional mean.

Parameters:
arLags - the AR lags
maLags - the MA lags
Returns:
the conditional mean

armaMean

public double armaMean(double[] arLags,
                       double[] maLags)
Compute the univariate ARMA conditional mean.

Parameters:
arLags - the AR lags
maLags - the MA lags
Returns:
the conditional mean

SuanShu, a Java numerical and statistical library

Copyright © 2011 Numerical Method Inc. Ltd. All Rights Reserved.