estBlackBox2 {dse1} | R Documentation

## Estimate a TSmodel

### Description

Estimate a TSmodel.

### Usage

        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)

### Arguments

`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 `informationTestsCalculations`.
`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.

### Details

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).

### Value

A TSestModel.

### References

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.

### See Also

`estBlackBox1`, `estBlackBox3` `estBlackBox4` `informationTestsCalculations`

### Examples

    if(is.R()) data("eg1.DSE.data.diff", package="dse1")
    z <-  estBlackBox2(eg1.DSE.data.diff)

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