estBlackBox2: Estimate a TSmodel
In dse: Dynamic Systems Estimation (Time Series Package)

Description Usage Arguments Details Value References See Also Examples

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 `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.

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