Synopses & Reviews
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.
Synopsis
Often a statistical analysis involves use of a set of alternative models for the data. A "model-selection criterion" is a formula which provides a figure-of merit for the alternative models. Generally the alternative models will involve different numhers of parameters. Model-selection criteria take into account hoth the goodness-or-fit of a model and the numher of parameters used to achieve that fit. 1.1. SETS OF ALTERNATIVE MODELS Thus the focus in this paper is on data-analytic situations ill which there is consideration of a set of alternative models. Choice of a suhset of explanatory variahles in regression, the degree of a polynomial regression, the number of factors in factor analysis, or the numher of dusters in duster analysis are examples of such situations. 1.2. MODEL SELECTION VERSUS HYPOTHESIS TESTING In exploratory data analysis or in a preliminary phase of inference an approach hased on model-selection criteria can offer advantages over tests of hypotheses. The model-selection approach avoids the prohlem of specifying error rates for the tests. With model selection the focus can he on simultaneous competition between a hroad dass of competing models rather than on consideration of a sequence of simpler and simpler models."
Table of Contents
Volume 1 Editor's General Preface. Preface. 1. Hirotugu Akaike, Statistical Scientist; E. Parzen. 2. Experiences on the Development of Time Series Models (Keynote lecture); H. Akaike. 3. State Space Modeling of Time Series; G. Kitagawa. 4. Autoregressive Model Fitting and Windows; M.B. Priestley. 5. System Analysis and Seasonal Adjustment through Model Fitting; M. Ishiguro. 6. Akaike's Approach can Yield Consistent Order Determination; H. Tong. 7. Recursive Order Selection for an ARMA Process; R.J. Bhansali. 8. Autoregressive Model Selection in Small Samples using a Bias-Corrected Version of AIC; C.M. Hurvich, C.L. Tsai. 9. Temporal Causality Measures based on AIC; W. Polasek. 10. An Automated Robust Method for Estimating Trend and Detecting Changes in Trend for Short Time Series; T. Atilgan. 11. Model Selection in Harmonic Non-Linear Regression; D. Haughton, J. Haughton, A. Izenman. 12. Dynamic Analysis of Japan's Economic Structure; S. Naniwa. 13. New Estimates of the Autocorrelation Coefficients of Stationary Sequences; S. Batalama, D, Kazakos. 14. Applications of TIMSAC; Y. Tamura. Volume 2 Editor's General Preface. Preface. 1. Some Aspects of Model-Selection Criteria; S.L. Sclove. 2. Mixture-Model Cluster Analysis using Model Selection Criteria and a new Informational Measure of Complexity; H. Bozdogan. 3. Information and Entropy in Cluster Analysis; H.H. Bock. 4. Information-Based Validity Functionals for Mixture Analysis; A.C. Cutler, M.P. Windham. 5. Unsupervised Classification with Stochastic Complexity; J. Rissanen, E.S. Ristad. 6. Modelling Principle Components with Structure; B.D. Flury, B. Neuenschwander. 7. AIC-Replacements for Some Multivariate Tests of Homogeneity with Applications in Multisample Clustering and Variable Selection; H. Bozdogan, S.L. Sclove, A.K. Gupta. 8. High Dimensional Covariance Estimation: Avoiding `The Curse of Dimensionality'; R.M. Pruzek. 9. Categorical Data Analysis by AIC; Y. Sakamoto. 10. Longitudinal Data Models with Fixed and Random Effects; R.H. Jones. 11. Multivariate Autoregressive Modeling for Analysis of Biomedical Systems with Feedback; T. Wada, T. Koyama, M. Shigemori. 12. A Simulation Study of Information Theoretic Techniques and Classical Hypothesis Tests in One Factor ANOVA; E.P. Rosenblum. Volume 3 Editor's General Preface. Preface. 1. Implications of Informational Point of View on the Development of Statistical Science (Keynote lecture); H. Akaike. 2. From Comparison Density to Two Sample Analysis; E. Parzen. 3. Statistical Identification and Optimal Control of Thermal Power Plants; H. Nakamura. 4. Applications of Autoregressive Model to Control Ship's Motions and Marine Engine; K. Ohtsu, G. Kitagawa. 5. Statistical Models for Earthquake Occurrence: Clusters, Cycles and Characteristic Earthquakes; D. Vere-Jones. 6. Seismological Applications of Statistical Methods for Point-Process Modelling; Y. Ogata. 7. One Channel at-a-Time Multichannel Autoregressive Modeling of Stationary and Nonstationary Time Series; W. Gersch, D. Stone. 8. Separation of Spin Synchronized Signals using a Bayesian Approach; T. Higuchi. 9. The Local Linearization Filter with Application to Nonlinear System Identifications; T. Ozaki. 10. Inference of Evolutionary Trees from DNA and Protein Sequence Data; M. Hasegawa. 11. New Structure Criteria in Group Method of Data Handling; T. Lange. 12. The Use of the Kullback--Leibler Distance for Learning in Neural Binary Classifiers; D. Pados, P. Papantoni-Kazakos, D. Kazakos, A. Koyiantis. Index.