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A Bayesian analysis of the minimum AIC procedure

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Summary

By using a simple example a minimax type optimality of the minimum AIC procedure for the selection of models is demonstrated.

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References

  1. Akaike, H. (1973). Information theory and an extension of the maximum likelihood principle,2nd International Symposium of Information Theory, B. N. Petrov and F. Csaki, eds., Akademiai Kiado, Budapest, 267–281.

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  2. Akaike, H. (1974). A new look at the statistical model identification,IEEE Trans. Automat. Contr., AC-19, 716–723.

    Article  MathSciNet  Google Scholar 

  3. Akaike, H. (1977). On entropy maximization principle,Applications of Statistics, P. R. Krishnaiah, ed., North-Holland, Amsterdam, 27–41.

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  4. Schwarz, G. (1976). Estimating the dimension of a model.Ann. Statist.,6, 461–464.

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The Institute of Statistical Mathematics

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Akaike, H. A Bayesian analysis of the minimum AIC procedure. Ann Inst Stat Math 30, 9–14 (1978). https://doi.org/10.1007/BF02480194

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  • DOI: https://doi.org/10.1007/BF02480194

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