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