Perform least squares estimation of a VAR model

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`x` |
A T-by-k matrix of k-dimensional time series |

`p` |
Order of VAR model. Default is 1. |

`output` |
A logical switch to control output. Default is with output. |

`include.mean` |
A logical switch. It is true if mean vector is estimated. |

`fixed` |
A logical matrix used in constrained estimation. It is used mainly in model simplifcation, e.g., removing insignificant estimates. |

To remove insignificant estimates, one specifies a threshold for individual t-ratio. The fixed matrix is then defined automatically to identify those parameters for removal.

`data ` |
Observed data |

`cnst ` |
A logical switch to include the mean constant vector |

`order ` |
VAR order |

`coef ` |
Coefficient matrix |

`aic,bic,hq` |
Information criteria of the fitted model |

`residuals` |
Residuals |

`secoef` |
Standard errors of the coefficients to be used in model refinement |

`Sigma ` |
Residual covariance matrix |

`Phi ` |
AR coefficient polynomial |

`Ph0 ` |
The constant vector |

Ruey S. Tsay

Tsay (2014, Chapter 3). Multivariate Time Series Analysis with R and Financial Applications. John Wiley. Hoboken, NJ.

refVAR command

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