est.black.box3 {dse2}R Documentation

Estimate a TSmodel

Description

Estimate a TSmodel.

Usage

    est.black.box3(data, estimation='est.VARX.ls', 
          lag.weight=1.0, 
          reduction='reduction.Mittnik', 
          criterion='aic', 
          trend=F, 
          subtract.means=F,  re.add.means=T, 
          standardize=F, verbose=T, max.lag=12, sample.start=10)

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. taic might be a better default selection criteria but it is not available for ARMA models.
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.
sample.start The starting point to use for calculating information criteria.

Details

VAR models are estimated for each lag up to the specified max.lag. From these the best is selected according to the specified criteria. The reduction procedure is then applied to this best model and the best reduced model selected. The default estimation procedure is least squares estimation of a VAR model.

Value

A TSestModel.

See Also

est.black.box1, est.black.box2 est.black.box4

Examples

if(is.R()) data("eg1.DSE.data.diff", package="dse1")
z <-  est.black.box3(eg1.DSE.data.diff)