est.black.box2 {dse2}R Documentation

Estimate a TSmodel

Description

Estimate a TSmodel.

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)

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 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.

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

est.black.box1, est.black.box3 est.black.box4

Examples

if(is.R()) data("eg1.DSE.data.diff", package="dse1")
z <-  est.black.box2(eg1.DSE.data.diff)