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Akaike or Bayesian information criteria

returns Akaike information
criteria (AIC) corresponding to optimized loglikelihood function
values (`aic`

= aicbic(`logL`

,`numParam`

)`logL`

), as returned by `estimate`

,
and the model parameters, `numParam`

.

[1] Box, G. E. P., G. M. Jenkins, and G. C.
Reinsel. *Time Series Analysis: Forecasting and Control*.
3rd ed. Englewood Cliffs, NJ: Prentice Hall, 1994.

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