dse (version 2014.11-1)

estBlackBox3: Estimate a TSmodel

Description

Estimate a TSmodel.

Usage

estBlackBox3(data, estimation='estVARXls', 
          lag.weight=1.0, 
          reduction='MittnikReduction', 
          criterion='aic', 
          trend=FALSE, 
          subtract.means=FALSE,  re.add.means=TRUE, 
          standardize=FALSE, verbose=TRUE, 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

Criterion to be used for model selection. see informationTestsCalculations. taic might be a better default selection criteria but it is not available for ARMA models.

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 T 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.

sample.start

The starting point to use for calculating information criteria.

Value

• A TSestModel.

concept

DSE

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.

See Also

estBlackBox1, estBlackBox2 estBlackBox4 informationTestsCalculations

Examples

data("eg1.DSE.data.diff", package="dse")
z <-  estBlackBox3(eg1.DSE.data.diff)