Proceedings of the First Us/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach : Volume 2 Multivariate Statistical Modeling

H. Bozdogan

ISBN 10: 0792325982 / ISBN 13: 9780792325987

Editore: Springer Dez 1993, 1993

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Neuware - 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.

Codice articolo 9780792325987

Dati bibliografici

• Titolo: Proceedings of the First Us/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach : Volume 2 Multivariate Statistical Modeling
• Editore: Springer Dez 1993
• Data di pubblicazione: 1993
• Lingua: Inglese
• ISBN 10: 0792325982
• ISBN 13: 9780792325987
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 28 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 28 millimetri di profondità
• Peso: 816 grammi

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Riassunto

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.

Contenuti

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.