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tswge (version 2.1.0)

aic.burg.wge: AR Model Identification using Burg Estimates

Description

AR model identification using either AIC, AICC, or BIC

Usage

aic.burg.wge(x, p = 1:5, type = "aic")

Value

type

Criterion used: aic (default), aicc, or bic

min_value

Value of the minimized criterion

p

AR order for selected model

phi

AR parameter estimates for selected model

vara

White noise variance estimate for selected model

Arguments

x

Realization to be analyzed

p

Range of p values to be considered

type

Type of model identification criterion: aic, aicc, or bic

Author

Wayne Woodward

References

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

Examples

Run this code
data(fig3.18a)
          aic.burg.wge(fig3.18a,p=1:5,type='aicc')

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