2006 Kyoto Prize Laureates

Basic Sciences

Mathematical Sciences(Including Pure Mathematics)

Hirotugu Akaike

/  Statistical Mathematician

1927 - 2009

Professor Emeritus, The Institute of Statistical Mathematics

Commemorative Lectures

The Use of Mathematics for Deciphering the Movement of an Object: A Historical Review of the Introduction of AIC

2006

11 /11 Sat

Place:Kyoto International Conference Center

Workshop

Major contribution to statistical science and modeling with the development of the Akaike Information Criterion (AIC)

2006

11 /12 Sun

13:00 - 17:20

Place:Kyoto International Conference Center

Achievement Digest

Major contribution to statistical science and modeling with the development of the Akaike Information Criterion (AIC)

In the early 1970’s, Dr. Hirotugu Akaike formulated the Akaike Information Criterion (AIC), a new practical, yet versatile criterion for the selection of statistical models, based on basic concepts of information mathematics. This criterion established a new paradigm that bridged the world of data and the world of modeling, thus contributing greatly to the information and statistical sciences.

*This field then was Field of Mathematical Sciences.

Citation

In the early 1970s, Dr. Hirotugu Akaike formulated the Akaike Information Criterion (AIC), a new practical, yet versatile criterion for the selection of statistical models, based on fundamental concepts of information mathematics. This criterion established a new paradigm that bridged the world of data and the world of modeling, thus contributing greatly to the information and statistical sciences.

Dr. Akaike derived the AIC based on the foundations of information mathematics, through the study of actual examples, including analysis of the processing of sericultural products, cement kiln controls, and thermal electric power plant controls, and the criterion gave a breakthrough solution to the model selection problem, a major problem common to any form of intellectual information processing. The AIC allows selecting a model that balances between the complexity of the model and goodness of its fit to the data. The AIC is widely used as a practical guideline for the selection of statistical models in a wide range of areas including medicine, epidemiology, biology, control engineering, economics, environmentology, geophysics and social sciences, as well as the fields of mathematics and statistics.

Dr. Akaike has multiple achievements, including the practical application of statistical control to various industrial plants, development of a modeling methodology in the time domain of multivariable time-series analysis, and development and promotion of the time-series analysis software TIMSAC. The widespread use of commercial statistics software packages that incorporate the idea and methodology of the AIC indicates the practicality and reliability of this criterion. Furthermore, Dr. Akaike identified the importance of the Bayesian model as early as the early 1980s, and contributed to the practical application of this model to the information and statistical sciences. Looking at the current growth of the Bayesian model in various fields that require intelligent information processing, more than 20 years after Dr. Akaike first recognized its importance, we cannot help being impressed by his scientific insight.

Today, thanks to the rapid progresses in information processing technologies, we are able to obtain an enormous amount of data and process it at a high speed. Extraction of knowledge and information, and the forecast and control of risk factors in human life have critical importance to the survival and development of human society. Based on the recognition of this situation, there is no doubt that Dr. Akaike’s criterion and the modeling methodology based thereon will become an increasingly important tool for humankind, and hence Dr. Akaike’s achievements deserve our greatest esteem.

For these reasons, the Inamori Foundation is pleased to present the 2006 Kyoto Prize in Basic Sciences to Dr. Hirotugu Akaike.

Profile

Biography
1927
Born in Fujinomiya, Shizuoka
1952
University of Tokyo, BA (Mathematics)
1952
Researcher, The Institute of Statistical Mathematics
1961
University of Tokyo, PhD
1962
Head of 2nd Section, 1st Division, The Institute of Statistical Mathematics
1973
Director of 5th Division, The Institute of Statistical Mathematics
1985
Head of Department of Prediction and Control, The Institute of Statistical Mathematics
1986
Director General, The Institute of Statistical MathematicsMember, Science Council of Japan (1988-1991)Professor, Department of Statistical Science, Graduate University for Advanced Studies (1988-1994)
1994
Emeritus Professor, The Institute of Statistical Mathematics
1994
Emeritus Professor, Graduate University for Advanced Studies
Selected Awards and Honors
1972
Ishikawa Prize, Union of Japanease Scientists and Engineers
1980
Okochi Memorial Technology Prize, Okochi Memorial Foundation
1989
1988 Asahi Prize, The Asahi Shimbun
1989
Purple Ribbon Medal (Japan)
1996
Japan Statistical Society Prize, Japan Statistical Society
Selected Publications
1969
Fitting autoregressive models for prediction, Ann.Inst.Statist.Math. 21: 243-247, 1969.
1970
Statistical prediction identification, Ann.Inst.Statist.Math. 22: 203-217, 1970.
1973
Information theory and an extension of the maximum likelihood principle, Proc.2nd International Symposium on Information Theory, Petrov, B. N. and Csaki, F.eds., Akademiai Kiado, Budapest, 267-281, 1973.
1974
A new look at the statistical model identification, IEEE Trans. Automat. Control. 19:716 - 723, 1974.
1977
On entropy maximization principle, in Applications of Statistics, Krishnaiah, P. R. ed., North-Holland Publishing Company, 27-41, 1977.

Profile is at the time of the award.

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