Performs the conditional maximum likelihood estimation of a VMA model with selected lags in the model

1 |

`da` |
A T-by-k matrix of a k-dimensional time series with T observations |

`malags` |
A vector consisting of non-zero MA lags |

`include.mean` |
A logical switch to include the mean vector |

`fixed` |
A logical matrix to fix coefficients to zero |

`prelim` |
A logical switch concerning initial estimation |

`details` |
A logical switch to control output level |

`thres` |
A threshold value for setting coefficient estimates to zero |

A modified version of VMA model by allowing the user to select non-zero MA lags

`data` |
The observed time series |

`MAlags` |
The VMA lags |

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

`coef` |
The parameter estimates |

`secoef` |
The standard errors of the estimates |

`residuals` |
Residual series |

`aic,bic` |
The information criteria of the fitted model |

`Sigma` |
Residual covariance matrix |

`Theta` |
The VMA matrix polynomial |

`mu` |
The mean vector |

`MAorder` |
The VMA order |

Ruey S. Tsay

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

VMA

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