Selected Papers of Hirotugu Akaike

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 mo...

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Bibliographic Details
Other Authors: Parzen, Emanuel (Editor), Tanabe, Kunio (Editor), Kitagawa, Genshiro (Editor)
Format: eBook
Published: New York, NY Springer New York 1998, 1998
Edition:1st ed. 1998
Series:Perspectives in Statistics
Online Access:
Collection: Springer Book Archives -2004 - Collection details see MPG.ReNa
Table of Contents:
  • Foreword
  • A Conversation with Hirotugu Akaike
  • List of Publications of Hirotugu Akaike
  • Papers
  • 1. Precursors
  • 1. On a zero-one process and some of its applications
  • 2. On a successive transformation of probability distribution and its application to the analysis of the optimum gradient method
  • 2. Frequency Domain Time Series Analysis
  • 1. Effect of timing-error on the power spectrum of sampled-data
  • 2. On a limiting process which asymptotically produces f-2 spectral density
  • 3. On the statistical estimation of frequency response function
  • 3. Time Domain Time Series Analysis
  • 1. On the use of a linear model for the identification of feedback systems
  • 2. Fitting autoregressive models for prediction
  • 3. Statistical predictor identification
  • 4. Autoregressive model fitting for control
  • 5. Statistical approach to computer control of cement rotary kilns
  • 6. Statistical identification for optimal control of supercritical thermal power plants
  • 6. General Views on Statistics
  • 1. Prediction and entropy
  • 2. Experiences on the development of time series models
  • 3. Implications of informational point of view on the development of statistical science
  • 4. AIC and Parametrization
  • 1. Information theory and an extension of the maximum likelihood princilple
  • 2. A new look at the statistical model identification
  • 3. Markovian representation of stochastic processes and its application to the analysis of autoregressive moving average processes
  • 4. Covariance matrix computation of the state variable of a stationary Gaussian process
  • 5. Analysis of cross classified data by AIC
  • 6. On linear intensity models for mixed doubly stochastic Poisson and self-exciting point processes
  • 5. Bayesian Approach
  • 1. A Baysian analysis of the minimum AIC procedure
  • 2. A new look at the Bayes procedure
  • 3. On the likelihood of a time series model
  • 4. Likelihood and the Bayes procedure
  • 5. Seasonal adjustment by a Bayesian modeling
  • 6. A quasi Bayesian approach to outlier detection
  • 7. On the fallacy of the likelihood principle
  • 8. A Bayesian apporach to the analysis of earth tides
  • 9. Factor analysis and AIC