public class VARMAModel extends VARIMAModel
| Constructor and Description |
|---|
VARMAModel(ARMAModel model)
Construct a multivariate model from a univariate ARMA model.
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VARMAModel(Matrix[] phi,
Matrix[] theta)
Construct a multivariate ARMA model with unit variance and zero-intercept (mu).
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VARMAModel(Matrix[] phi,
Matrix[] theta,
Matrix sigma)
Construct a multivariate ARMA model with zero-intercept (mu).
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VARMAModel(VARMAModel that)
Copy constructor.
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VARMAModel(Vector mu,
Matrix[] phi,
Matrix[] theta)
Construct a multivariate ARMA model with unit variance.
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VARMAModel(Vector mu,
Matrix[] phi,
Matrix[] theta,
Matrix sigma)
Construct a multivariate ARMA model.
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| Modifier and Type | Method and Description |
|---|---|
Vector |
conditionalMean(Matrix arLags,
Matrix maLags)
Compute the multivariate ARMA conditional mean, given all the lags.
|
VARMAModel |
getDemeanedModel()
Get the demeaned version of the time series model.
|
Vector |
unconditionalMean()
Compute the multivariate ARMA unconditional mean.
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getVARMApublic VARMAModel(Vector mu, Matrix[] phi, Matrix[] theta, Matrix sigma)
mu - the intercept (constant) vectorphi - the AR coefficients (excluding the initial 1); null if no AR coefficienttheta - the MA coefficients (excluding the initial 1); null if no MA coefficientsigma - the white noise covariance matrixpublic VARMAModel(Vector mu, Matrix[] phi, Matrix[] theta)
mu - the intercept (constant) vectorphi - the AR coefficients (excluding the initial 1); null if no AR coefficienttheta - the MA coefficients (excluding the initial 1); null if no MA coefficientpublic VARMAModel(Matrix[] phi, Matrix[] theta, Matrix sigma)
phi - the AR coefficients (excluding the initial 1); null if no AR coefficienttheta - the MA coefficients (excluding the initial 1); null if no MA coefficientsigma - the white noise covariance matrixpublic VARMAModel(Matrix[] phi, Matrix[] theta)
phi - the AR coefficients (excluding the initial 1); null if no AR coefficienttheta - the MA coefficients (excluding the initial 1); null if no MA coefficientpublic VARMAModel(ARMAModel model)
model - a univariate ARMA modelpublic VARMAModel(VARMAModel that)
that - a multivariate ARMA modelpublic Vector conditionalMean(Matrix arLags, Matrix maLags)
arLags - the AR lagsmaLags - the MA lagspublic Vector unconditionalMean()
public VARMAModel getDemeanedModel()
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