A Bayesian analysis of the minimum AIC procedure

  • Hirotugu Akaike
Article

Summary

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

Keywords

Posterior Distribution Multivariate Gaussian Distribution Entropy Maximization Principle Maximum Likeli Marginal Posterior Distribution 
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References

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    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.Google Scholar
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    Akaike, H. (1974). A new look at the statistical model identification,IEEE Trans. Automat. Contr., AC-19, 716–723.MATHMathSciNetCrossRefGoogle Scholar
  3. [3]
    Akaike, H. (1977). On entropy maximization principle,Applications of Statistics, P. R. Krishnaiah, ed., North-Holland, Amsterdam, 27–41.Google Scholar
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    Schwarz, G. (1976). Estimating the dimension of a model.Ann. Statist.,6, 461–464.Google Scholar

Copyright information

© Kluwer Academic Publishers 1978

Authors and Affiliations

  • Hirotugu Akaike

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