est.black.box4 {dse2}R Documentation

Estimate a TSmodel

Description

Estimate a TSmodel with Brute Force Technique.

Usage

    est.black.box4(data, estimation="est.VARX.ls", 
                lag.weight=1.0,  variable.weights=1, 
                reduction="reduction.Mittnik", 
                criterion="taic", 
                trend=F, subtract.means=F,  re.add.means=T, 
                standardize=F, verbose=T, max.lag=12, sample.start=10, warn=T)
    bft(data, ... )

Arguments

data A TSdata object.
estimation A character string indicating the estimation method to use.
lag.weight Weighting to apply to lagged observations.
variable.weights Weighting to apply to series if estimation method is est.wt.variables.
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 VAR estimation is done for each lag up to max.lag.
sample.start The starting point to use for calculating information criteria in the final selection.

Details

For each lag up to max.lag a VAR model is estimated and then a reduction procedure applied to select the best reduced model. Finally the best of the best reduced models is selected. The default estimation procedure is least squares estimation of the VAR models. This procedure is described as the brute force technique (bft) 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.box2 est.black.box3

Examples

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