Born: November 5, 1927, Shizuoka Prefecture, Japan.

Died: August 4, 2009, Ibaraki Prefecture, Japan.

Higher Education: BA and PhD in Mathematics at University of Tokyo (Tokyo, Japan).

Main Publications: 

• Akaike, H. (1969), “Fitting autoregressive models for prediction” (PDF), Annals of the Institute of Statistical Mathematics, 21: pp. 243–247
• Akaike, H. (1970), “Statistical predictor identification” (PDF), Annals of the Institute of Statistical Mathematics, 22: pp. 203–277
• Akaike, H. (1973), “Information theory and an extension of the maximum likelihood principle”, in Petrov, B. N.; Csáki, F. (eds.), 2nd International Symposium on Information Theory, Tsahkadsor, Armenia, USSR, September 2-8, 1971, Budapest: Akadémiai Kiadó, pp. 267–281; republished in Kotz, S.; Johnson, N. L., eds. (1992), Breakthroughs in Statistics, I, Springer-Verlag, pp. 610–624
• Akaike, H. (1973), “Maximum likelihood identification of Gaussian autoregressive moving average models” (PDF), Biometrika, 60 (2): pp. 255–265
• Akaike, H. (1974), “A new look at the statistical model identification”, IEEE Transactions on Automatic Control, 19 (6): pp. 716–723
• Akaike, H. (1975), “Block Toeplitz matrix inversion”, SIAM Journal on Applied Mathematics, 24 (2): pp. 234–241
• Akaike, H. (1975), “Markovian representation of stochastic processes by canonical variables”, SIAM Journal on Control, 13: pp. 162–173
• Akaike, H. (1976), “Canonical correlation analysis of time series and the use of an information criterion”, in Mehra, R. K.; Lainiotis, D. G. (eds.), System Identification: Advances and Case Studies, Academic Press, pp. 27–96
• Akaike, H. (1977), “On entropy maximization principle”, in Krishnaiah, P. R. (ed.), Applications of statistics, North-Holland Publishing Company, pp. 27–41
• Akaike, H. (1978), “A new look at the Bayes procedure”, Biometrika, 65 (1): pp. 53–59
• Akaike, H. (1978), “A Bayesian analysis of the minimum AIC procedure” (PDF), Annals of the Institute of Statistical Mathematics, 30: pp. 9–14
• Akaike, H. (1978), “On the likelihood of a time series model”, The Statistician, 27 (3/4): pp. 217–235
• Akaike, H. (1979), “A Bayesian extension of the minimum AIC procedure of autoregressive model fitting”, Biometrika, 66 (2): pp. 237–242
• Akaike, H. (1980). “Likelihood and the Bayes procedure (with discussion)”. J. M. Bernardo, M. H. DeGroot, D. V. Lindley, and A. F. M. Smith (eds.) Bayesian Statistics, pp. 143–203, Valencia, Spain: University Press
• Akaike, H. (1981), “Likelihood of a model and information criteria” (PDF), Journal of Econometrics, 16: pp. 3–14
• Akaike, H. (1981). “Modern development of statistical methods”. P. Eykhoff (ed.) Trends and Progress in System Identification, pp. 169–184. Pergamon Press
• 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, pp. 165–189. Academic Press
• Akaike, H. (1983). “Information measures and model selection”. Proceedings of the 44th World Statistics Congress of the International Statistical Institute, pp. 277–291
• Akaike, H. (1983), “On minimum information prior distributions” (PDF), Annals of the Institute of Statistical Mathematics, 35 (2): pp. 139–149
• Akaike, H. (1985). “Prediction and entropy”. A. C. Atkinson, and S. E. Fienberg (eds.) A Celebration of Statistics, pp. 1–24. Springer
• Akaike, H. (1987), “Factor analysis and AIC”, Psychometrika, 52 (3): pp. 317–332
• Akaike, H. (1994), “Implications of informational point of view on the development of statistical science”, in Bozdogan, H. (ed.), Proceedings of the First US/JAPAN Conference on The Frontiers of Statistical Modeling: An Informational Approach—Volume 3, Kluwer Academic Publishers, pp. 27–38.

Knows for:

• Akaike information criterion (AIC).