aic5.ar.wge {tswge} | R Documentation |
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)
[Package tswge version 2.1.0 Index]