Selected Papers of Hirotugu Akaike

1. Front Matter

   Pages i-viii

   PDF

2. Foreword

   1. Foreword

      • Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawa

      Pages 1-2

3. A Conversation with Hirotugu Akaike

   1. A Conversation with Hirotugu Akaike

      • David F. Findley, Emanuel Parzen

      Pages 3-16

4. List of Publications of Hirotugu Akaike

   1. List of Publications of Hirotugu Akaike

      • Emanuel Parzen, Kunio Tanabe, Genshiro Kitagawa

      Pages 17-28

5. Papers

   1. Precursors

      1. On a Zero-One Process and Some of Its Applications

         • Hirotugu Akaike

         Pages 29-36

      2. On a Successive Transformation of Probability Distribution and Its Application to the Analysis of the Optimum Gradient Method

         • Hirotugu Akaike

         Pages 37-52

   2. Frequency Domain Time Series Analysis

      1. Effect of Timing-Error on the Power Spectrum of Sampled-Data

         • Hirotugu Akaike

         Pages 53-73

      2. On a Limiting Process Which Asymptotically Produces <i>f</i> ^-2 Spectral Density

         • Hirotugu Akaike

         Pages 75-79

      3. On the Statistical Estimation of Frequency Response Function

         • Hirotugu Akaike, Yasufumi Yamanouchi

         Pages 81-114

   3. Time Domain Time Series Analysis

      1. On the Use of a Linear Model for the Identification of Feedback Systems

         • Hirotugu Akaike

         Pages 115-129

      2. Fitting Autoregreesive Models for Prediction

         • Hirotugu Akaike

         Pages 131-135

      3. Statistical Predictor Identification

         • Hirotugu Akaike

         Pages 137-151

      4. Autoregressive Model Fitting for Control

         • Hirotugu Akaike

         Pages 153-170

      5. Statistical Approach to Computer Control of Cement Rotary Kilns

         • T. Otomo, T. Nakagawa, H. Akaike

         Pages 171-184

      6. Statistical Identification for Optimal Control of Supercritical Thermal Power Plants

         • H. Nakamura, H. Akaike

         Pages 185-197

   4. AIC and Parametrization

      1. Information Theory and an Extension of the Maximum Likelihood Principle

         • Hirotogu Akaike

         Pages 199-213

      2. A New Look at the Statistical Model Identification

         • Hirotugu Akaike

         Pages 215-222

      3. Markovian Representation of Stochastic Processes and Its Application to the Analysis of Autoregressive Moving Average Processes

         • Hirotugu Akaike

         Pages 223-247

      4. Covariance Matrix Computation of the State Variable of a Stationary Gaussian Process

         • Hirotugu Akaike

         Pages 249-254

      5. Analysis of Cross Classified Data by AIC

         • Yosiyuki Sakamoto, Hirotugu Akaike

         Pages 255-267

The pioneering research of Hirotugu Akaike has an international reputation for profoundly affecting how data and time series are analyzed and modelled and is highly regarded by the statistical and technological communities of Japan and the world. His 1974 paper "A new look at the statistical model identification" (IEEE Trans Automatic Control, AC-19, 716-723) is one of the most frequently cited papers in the area of engineering, technology, and applied sciences (according to a 1981 Citation Classic of the Institute of Scientific Information). It introduced the broad scientific community to model identification using the methods of Akaike's criterion AIC. The AIC method is cited and applied in almost every area of physical and social science. The best way to learn about the seminal ideas of pioneering researchers is to read their original papers. This book reprints 29 papers of Akaike's more than 140 papers. This book of papers by Akaike is a tribute to his outstanding career and a service to provide students and researchers with access to Akaike's innovative and influential ideas and applications. To provide a commentary on the career of Akaike, the motivations of his ideas, and his many remarkable honors and prizes, this book reprints "A Conversation with Hirotugu Akaike" by David F. Findley and Emanuel Parzen, published in 1995 in the journal Statistical Science. This survey of Akaike's career provides each of us with a role model for how to have an impact on society by stimulating applied researchers to implement new statistical methods.

• Covariance matrix
• Factor analysis
• Fitting
• Probability distribution
• STATISTICA
• Time series
• best fit
• information theory
• linear optimization
• statistics

• Department of Statistics, Texas A&M University, College Station, USA

  Emanuel Parzen

• The Institute of Statistical Mathematics, Minato-ku Tokyo, Japan

  Kunio Tanabe, Genshiro Kitagawa

Policies and ethics