These three volumes comprise the proceedings of the US/Japan Conference, held in honour of Professor H. Akaike, on the `Frontiers of Statistical Modeling: an Informational Approach'. The major theme of the conference was the implementation of statistical modeling through an informational approach to complex, real-world problems.
Volume 1 contains papers which deal with the Theory and Methodology of Time Series Analysis. Volume 1 also contains the text of the Banquet talk by E. Parzen and the keynote lecture of H. Akaike. Volume 2 is devoted to the general topic of Multivariate Statistical Modeling, and Volume 3 contains the papers relating to Engineering and Scientific Applications.
For all scientists whose work involves statistics.
Inhaltsverzeichnis
of Volume 1. - Summary of Contributed Papers to Volume 1. - 1. Hirotugu Akaike, Statistical Scientist. - 2. Experiences on the Development of Time Series Models (Keynote lecture). - 3. State Space Modeling of Time Series. - 4. Autoregressive Model Fitting and Windows. - 5. System Analysis and Seasonal Adjustment Through Model Fitting. - 6. Akaike s Approach Can Yield Consistent Order Determination. - 7. Recursive Order Selection for an ARMA Process. - 8. Autoregressive Model Selection in Small Samples Using a Bias-Corrected Version of AIC. - 9. Temporal Causality Measures Based on AIC. - 10. An Automated Robust Method for Estimating Trend and Detecting Changes in Trend for Short Time Series. - 11. Model Selection in Harmonic Non-Linear Regression. - 12. Dynamic Analysis of Japan s Economic Structure. - 13. New Estimates of the Autocorrelation Coefficients of Stationary Sequences. - 14. Applications of TIMSAC. - Index to Volume 1.
