est.black.box2
Estimate a TSmodel
Description
Usage
est.black.box2(data, estimation='est.VARX.ls',
lag.weight=.9,
reduction='reduction.Mittnik',
criterion='taic',
trend=F,
subtract.means=F, re.add.means=T,
standardize=F, verbose=T, max.lag=12)
Required Arguments
Optional Arguments
- 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
-
Character string indicating model selection criteria.
- trend
-
If T include a trend in the model.
- subtract.means
-
If T the mean is subtracted from the data before estimation.
- re.add.means
-
If subtract.means is T then if re.add.means is T the estimated model is
converted back to a model for data without the mean subtracted.
- standardize
-
If T the data is transformed so that all variables have the same variance.
- verbose
-
If T then additional information from the estimation and reduction procedures is printed.
- max.lag
-
The number of lags to include in the VAR estimation.
Value
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
P.Gilbert 'Combining VAR Estimation and State Space Model Reduction for
Simple Good Predictions' forethcoming in J. of Forecasting (1995?).
See Also
Examples
z <- est.black.box2(data)
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