Akaike_Guest_House_in_Jan_2016
Akaike_Guest_House_in_Jan_2016

Hirotugu Akaike  (November 5, 1927 – August 4, 2009) was a Japanese statistician. In the early 1970s, he formulated a criterion for model selection—the Akaike information criterion, which is now widely used.

 

Awards


In 2006 Akaike was awarded the Kyoto Prize for his major contribution to statistical science and modeling in the development of the Akaike Information Criterion (AIC). Today Google is showing a Doodle for Hirotugu Akaike’s 90th Birthday.

Publications


  • Akaike, Hirotugu (December 1974). “A new look at the statistical model identification”. IEEE Transactions on Automatic Control

  • Akaike, H. (1976). Canonical correlation analysis of time series and the use of an information criterion. R.K. Mehra, and D.G. Lainiotis (eds.) System Identification: Advances and Case Studies, 27–96. Academic Press, New York, NY.

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

  • Akaike, H. (1978). A new look at the Bayes procedure. Biometrika

  • Akaike, H. (1978). A Bayesian analysis of the minimum AIC procedure. Annals of the Institute of Statistical Mathematics 30, 9–14.

  • Akaike, H. (1978). On the likelihood of a time series model. The Statistician 27, 217–235.

  • Akaike, H. (1979). A Bayesian extension of the minimum AIC procedure of autoregressive model fitting. Biometrika 66, 237–242.

  • Akaike, H. (1980). Likelihood and the Bayes procedure (with discussion). J.M. Bernardo, M.H. De Groot, D.V. Lindley, and A.F.M. Smith (eds.) Bayesian Statistics, 143–203. University Press, Valencia, Spain.

  • Akaike, H. (1981). Likelihood of a model and information criteria. Journal of Econometrics 16, 3–14.

  • Akaike, H. (1981). The modern development of statistical methods. P. Eykhoff (ed.) Trends and Progress in System Identification, 169–184. Pergamon Press, Paris.

  • Akaike, H. (1983). Statistical inference and measurement of entropy. G.E.P. Box, T. Leonard, and C-F. Wu (eds.) Scientific Inference, Data Analysis, and Robustness, 165–189. Academic Press, London.

  • Akaike, H. (1983). Information measures and model selection. International Statistical Institute 44, 277–291.

  • Akaike, H. (1983). On minimum information prior distributions. Annals of the Institute of Statistical Mathematics 35A, 139–149.

  • Akaike, H. (1985). Prediction and entropy. A.C. Atkinson, and S.E. Fienberg (eds.) A Celebration of Statistics, 1–24. Springer, New York, NY.

  • Akaike, H. (1987). Factor analysis and AIC. Psychometrika 52, 317–332.

  • Akaike, H. (1992). Information theory and an extension of the maximum likelihood principle. S. Kotz, and N.L. Johnson (eds.) Breakthroughs in Statistics, Vol.1: 610–624. Springer-Verlag, London.

  • Hirotugu Akaike and Toichiro Nakagawa (1988), Statistical analysis and control of dynamic systems, Tokyo, Dordrecht: KTK Scientific; London: Kluwer. ISBN 90-277-2786-4. (Translation of 1972 book in Japanese.)

  • Selected papers of Hirotugu Akaike (edited by Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawa), New York: Springer, 1998. ISBN 0-387-98355-4.


 

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