estBlackBox2 {dse} | R Documentation |

Estimate a TSmodel.

```
estBlackBox2(data, estimation='estVARXls',
lag.weight=.9,
reduction='MittnikReduction',
criterion='taic',
trend=FALSE,
subtract.means=FALSE, re.add.means=TRUE,
standardize=FALSE, verbose=TRUE, max.lag=12)
```

`data` |
a TSdata object. |

`estimation` |
a character string indicating the estimation method to use. |

`lag.weight` |
weighting to apply to lagged observations. |

`reduction` |
character string indicating reduction procedure to use. |

`criterion` |
criterion to be used for model
selection. see |

`trend` |
if TRUE include a trend in the model. |

`subtract.means` |
if TRUE the mean is subtracted from the data before estimation. |

`re.add.means` |
if subtract.means is TRUE then if re.add.means is TRUE the estimated model is converted back to a model for data without the mean subtracted. |

`standardize` |
if TRUE the data is transformed so that all variables have the same variance. |

`verbose` |
if TRUE then additional information from the estimation and reduction procedures is printed. |

`max.lag` |
The number of lags to include in the VAR estimation. |

A model is estimated and then a reduction procedure applied. The default estimation procedure is least squares estimation of a VAR model with lagged values weighted. This procedure is discussed in Gilbert (1995).

A TSestModel.

Gilbert, P.D. (1995) Combining VAR Estimation and State Space
Model Reduction for Simple Good Predictions *J. of Forecasting:
Special Issue on VAR Modelling*, **14**, 229–250.

`estBlackBox1`

,
`estBlackBox3`

`estBlackBox4`

`informationTestsCalculations`

```
data("eg1.DSE.data.diff", package="dse")
z <- estBlackBox2(eg1.DSE.data.diff)
```

[Package *dse* version 2020.2-1 Index]