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Use Different Criteria for Model Selection 

Select a time series model for data based on different selection criteria, such as Akaike information criterion (AIC), finite sample corrected AIC, Bayesian information criterion (BIC), or Schwarz–Bayes information criterion (SBC).

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Display the table of the ranked candidate models for each criterion.

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Select the top three entries from each table and refine them using the maximum likelihood estimation. Models estimated with different methods may have different rankings.

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Define ranking function for each criterion.

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Select the best maximum likelihood estimates according to different criteria.

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