VARModel (NM DEV API (v1.2.4) by NM)

java.lang.Object
- dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAXModel
- - dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel
  - - dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel
    - - dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARModel

Direct Known Subclasses:

SimpleAR1Fit, VARFit, VARLinearRepresentation
```
public class VARModel
extends VARMAModel
```
This class represents a VAR model.

See Also:

Wikipedia: Vector autoregressive model

Constructor Summary

Constructors
Constructor	Description
`VARModel(Matrix[] phi)`	Construct a VAR model with unit variance and zero-intercept (mu).
`VARModel(Matrix[] phi, Matrix sigma)`	Construct a VAR model with zero-intercept (mu).
`VARModel(Vector mu, Matrix[] phi)`	Construct a VAR model with unit variance.
`VARModel(Vector mu, Matrix[] phi, Matrix sigma)`	Construct a VAR model.
`VARModel(VARModel that)`	Copy constructor.
`VARModel(ARModel model)`	Construct a multivariate model from a univariate AR model.

Method Summary
- Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.stationaryprocess.arma.VARMAModel
  conditionalMean, getDemeanedModel, unconditionalMean
- Methods inherited from class dev.nm.stat.timeseries.linear.multivariate.arima.VARIMAModel
  getVARMA
- 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
  - VARModel
```
public VARModel(Vector mu,
                Matrix[] phi,
                Matrix sigma)
```
    Construct a VAR model.
    
    Parameters:
    
    mu - the intercept (constant) vector
    
    phi - the AR coefficients (excluding the initial 1)
    
    sigma - the white noise covariance matrix
  - VARModel
```
public VARModel(Vector mu,
                Matrix[] phi)
```
    Construct a VAR model with unit variance.
    
    Parameters:
    
    mu - the intercept (constant) vector
    
    phi - the AR coefficients (excluding the initial 1)
  - VARModel
```
public VARModel(Matrix[] phi,
                Matrix sigma)
```
    Construct a VAR model with zero-intercept (mu).
    
    Parameters:
    
    phi - the AR coefficients (excluding the initial 1)
    
    sigma - the white noise covariance matrix
  - VARModel
```
public VARModel(Matrix[] phi)
```
    Construct a VAR model with unit variance and zero-intercept (mu).
    
    Parameters:
    
    phi - the AR coefficients (excluding the initial 1)
  - VARModel
```
public VARModel(ARModel model)
```
    Construct a multivariate model from a univariate AR model.
    
    Parameters:
    
    model - a univariate AR model
  - VARModel
```
public VARModel(VARModel that)
```
    Copy constructor.
    
    Parameters:
    
    that - a VAR model