est.black.box2 {dse2} | R Documentation |
Estimate a TSmodel.
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)
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 |
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. |
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.
est.black.box1
,
est.black.box3
est.black.box4
if(is.R()) data("eg1.DSE.data.diff", package="dse1") z <- est.black.box2(eg1.DSE.data.diff)