Learn R Programming

dse (version 2014.11-1)

estBlackBox2: Estimate a TSmodel

Description

Estimate a TSmodel.

Usage

estBlackBox2(data, estimation='estVARXls', 
          lag.weight=.9, 
          reduction='MittnikReduction', 
          criterion='taic', 
          trend=FALSE, 
          subtract.means=FALSE,  re.add.means=TRUE, 
          standardize=FALSE, verbose=TRUE, 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
criterion to be used for model selection. see informationTestsCalculations.
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 TRUE 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.

Value

  • A TSestModel.

concept

DSE

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).

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

estBlackBox1, estBlackBox3 estBlackBox4 informationTestsCalculations

Examples

Run this code
data("eg1.DSE.data.diff", package="dse")
z <-  estBlackBox2(eg1.DSE.data.diff)

Run the code above in your browser using DataLab