aic5.ar.wge: Return top 5 AIC, AICC, or BIC picks for AR model fits

In BivinSadler/tswge: Time Series for Data Science

Return top 5 AIC, AICC, or BIC picks for AR model fits

Description

You may select either AIC, AICC, or BIC to use model identification. You can also used ML, Burg, or Yule-Walker estimates. Given a range of values for p and q, the program returns the top 5 candidate models.

Usage

aic5.ar.wge(x, p = 0:5, type = "aic",method='mle')

Arguments

x	Realization to model
p	Range of AR orders to be considered
type	Either 'aic' (default), 'aicc', or 'bic'
method	Either 'MLE' (default), 'Burg', or 'YW'

Value

A list of p, selected criterion for the top 5 models. The identification type and estimation method are printed on the output.

Note

If some model order combinations give explosively nonstationary models, then the program may stop prematurely. You may need to adjust the range of p and q to avoid these models.

Author(s)

Wayne Woodward

References

"Applied Time Series Analysis with R, 2nd edition" by Woodward, Gray, and Elliott

Examples

data(fig3.18a)
          aic5.wge(fig3.18a,p=0:5,q=0:2)

BivinSadler/tswge documentation built on Sept. 15, 2023, 4:07 p.m.