Class VARXModel
- java.lang.Object
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- dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel
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- dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAXModel
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- dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARXModel
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public class VARXModel extends VARMAXModel
A VARX (Vector AutoRegressive model with eXogeneous inputs) model, Xt, takes this form. \[ Y_t = \mu + \Sigma \phi_i * Y_{t-i} + \Psi * D_t + \epsilon_t \] where Yt, μ and εt are n-dimensional vectors. The n-by-n matrices {φi} (i = 1, 2, ..., p) denote the AR coefficients. Dt is an m-by-1 vector which contains all exogenous variables at time t (excluding the intercept term), and its coefficients are represented by an n-by-m matrix ψ. This implementation provides conversion methods between a VARX(p) model and a VECM(p) model (long-run or transitory).- See Also:
- "S. Johansen, "ch. 2-4, pp. 11-88," Likelihood-Based Inference in Cointegrated Vector Autoregressive Models, Oxford, Oxford University Press, 1995."
- "S. Johansen and K. Juselius, Maximum Likelihood Estimation and Inference on Cointegration - with Applications to the Demand for Money, Oxford Bull. of Econ. and Stat, vol. 52, 169-210, 1990."
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Constructor Summary
Constructors Constructor Description VARXModel(Matrix[] phi, Matrix psi)
Construct a VARX model with unit variance and zero-mean.VARXModel(Matrix[] phi, Matrix psi, Matrix sigma)
Construct a VARX model with zero-mean.VARXModel(Vector mu, Matrix[] phi, Matrix psi)
Construct a VARX model with unit variance.VARXModel(Vector mu, Matrix[] phi, Matrix psi, Matrix sigma)
Construct a VARX model.VARXModel(VARXModel that)
Copy constructor.VARXModel(VECMLongrun vecm)
Construct a VARX(p) from a long-run VECM(p).VARXModel(VECMTransitory vecm)
Construct a VARX(p) from a transitory VECM(p).
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Constructor Detail
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VARXModel
public VARXModel(Vector mu, Matrix[] phi, Matrix psi, Matrix sigma)
Construct a VARX model.- Parameters:
mu
- the intercept (constant) vectorphi
- the AR coefficients (excluding the initial 1)psi
- the coefficients of the deterministic terms (excluding the intercept)sigma
- the white noise covariance matrix
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VARXModel
public VARXModel(Vector mu, Matrix[] phi, Matrix psi)
Construct a VARX model with unit variance.- Parameters:
mu
- the intercept (constant) vectorphi
- the AR coefficients (excluding the initial 1)psi
- the coefficients of the deterministic terms (excluding the intercept)
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VARXModel
public VARXModel(Matrix[] phi, Matrix psi, Matrix sigma)
Construct a VARX model with zero-mean.- Parameters:
phi
- the AR coefficients (excluding the initial 1)psi
- the coefficients of the deterministic terms (excluding the intercept)sigma
- the white noise covariance matrix
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VARXModel
public VARXModel(Matrix[] phi, Matrix psi)
Construct a VARX model with unit variance and zero-mean.- Parameters:
phi
- the AR coefficients (excluding the initial 1)psi
- the coefficients of the deterministic terms (excluding the intercept)
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VARXModel
public VARXModel(VECMTransitory vecm)
Construct a VARX(p) from a transitory VECM(p).- Parameters:
vecm
- a transitory VECM(p)
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VARXModel
public VARXModel(VECMLongrun vecm)
Construct a VARX(p) from a long-run VECM(p).- Parameters:
vecm
- a long-run VECM(p)
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VARXModel
public VARXModel(VARXModel that)
Copy constructor.- Parameters:
that
- a VARX model
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