dse (version 2020.2-1)

bestTSestModel: Select Best Model

Description

Select the best model.

Usage

bestTSestModel(models, sample.start=10, sample.end=NULL,
     criterion='aic', verbose=TRUE)

Arguments

models

a list of TSestModels.

sample.start

the starting point to use for calculating information criteria.

sample.end

the end point to use for calculating information criteria.

criterion

Criterion to be used for model selection. see informationTestsCalculations. 'taic' would be a better default but this is not available for VAR and ARMA models.

verbose

if TRUE then additional information is printed.

Value

A TSestModel

Details

Information criteria are calculated and return the best model from ... according to criterion models should be a list of TSestModel's. models[[i]]$estimates$pred is not recalculated but a sub-sample identified by sample.start and sample.end is used and the likelihood is recalculated. If sample.end=NULL data is used to the end of the sample. taic might be a better default selection criteria but it is not available for ARMA models.

See Also

estBlackBox1, estBlackBox2 estBlackBox3 estBlackBox4 informationTestsCalculations

Examples

# NOT RUN {
data("eg1.DSE.data.diff", package="dse")
models <- list(estVARXls(eg1.DSE.data.diff), estVARXar(eg1.DSE.data.diff))
z <-  bestTSestModel(models)
# }