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Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

Volume 2 Multivariate Statistical Modeling

  • Conference proceedings
  • © 1994

Overview

Editors:
  1. Hamparsum Bozdogan

    1. Department of Statistics, The University of Tennessee, Knoxville, USA

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  2. Stanley L. Sclove

    1. Department of Information & Decision Sciences M/C 294, CBA, University of Illinois at Chicago, Chicago, USA

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  3. Arjun K. Gupta

    1. Department of Mathematics & Statistics, Bowling Green State University, Bowling Green, USA

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  4. D. Haughton

    1. Department of Mathematical Sciences, Bentley College, Waltham, USA

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  5. G. Kitagawa

    1. The Institute of Statistical Mathematics, Tokyo, Japan

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  6. T. Ozaki

    1. The Institute of Statistical Mathematics, Tokyo, Japan

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  7. K. Tanabe

    1. The Institute of Statistical Mathematics, Tokyo, Japan

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Table of contents (15 papers)

  1. Front Matter

    Pages i-xiii
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  2. Summary of Contributed Papers to Volume 2

    • Stanley L. Sclove
    Pages 1-35

  3. Some Aspects of Model-Selection Criteria

    • Stanley L. Sclove
    Pages 37-67

  4. Mixture-Model Cluster Analysis Using Model Selection Criteria and a New Informational Measure of Complexity

    • Hamparsum Bozdogan
    Pages 69-113

  5. Information and Entropy in Cluster Analysis

    • H. H. Bock
    Pages 115-147

  6. Information-Based Validity Functionals for Mixture Analysis

    • Adele Cutler, Michael P. Windham
    Pages 149-170

  7. Unsupervised Classification with Stochastic Complexity

    • Jorma Rissanen, Eric Sven Ristad
    Pages 171-182

  8. Modelling Principal Components with Structure

    • Bernard D. Flury, Beat E. Neuenschwander
    Pages 183-198

  9. Aic-Replacements for Some Multivariate Tests of Homogeneity with Applications in Multisample Clustering and Variable Selection

    • Hamparsum Bozdogan, Stanley L. Sclove, Arjun K. Gupta
    Pages 199-232

  10. High Dimensional Covariance Estimation: Avoiding the ‘Curse of Dimensionality’

    • Robert M. Pruzek
    Pages 233-253

  11. Categorical Data Analysis by AIC

    • Y. Sakamoto
    Pages 255-269

  12. Longitudinal Data Models with Fixed and Random Effects

    • Richard H. Jones
    Pages 271-292

  13. Multivariate Autoregressive Modeling for Analysis of Biomedical Systems with Feedback

    • T. Wada, T. Koyama, M. Shigemori
    Pages 293-317

  14. A Simulation Study of Information Theoretic Techniques and Classical Hypothesis Tests in One Factor Anova

    • Elizabeth P. Rosenblum
    Pages 319-346

  15. Roles of Fisher Type Information in Latent Trait Models

    • F. Samejima
    Pages 347-378

  16. A Review of Applications of Aic in Psychometrics

    • Y. Takane
    Pages 379-403

  17. Back Matter

    Pages 405-417
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Keywords

About this book

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.

Editors and Affiliations

  • Department of Statistics, The University of Tennessee, Knoxville, USA

    Hamparsum Bozdogan

  • Department of Information & Decision Sciences M/C 294, CBA, University of Illinois at Chicago, Chicago, USA

    Stanley L. Sclove

  • Department of Mathematics & Statistics, Bowling Green State University, Bowling Green, USA

    Arjun K. Gupta

  • Department of Mathematical Sciences, Bentley College, Waltham, USA

    D. Haughton

  • The Institute of Statistical Mathematics, Tokyo, Japan

    G. Kitagawa, T. Ozaki, K. Tanabe

Bibliographic Information

  • Book Title: Proceedings of the First US/Japan Conference on the Frontiers of Statistical Modeling: An Informational Approach

  • Book Subtitle: Volume 2 Multivariate Statistical Modeling

  • Editors: Hamparsum Bozdogan, Stanley L. Sclove, Arjun K. Gupta, D. Haughton, G. Kitagawa, T. Ozaki, K. Tanabe

  • DOI: https://doi.org/10.1007/978-94-011-0800-3

  • Publisher: Springer Dordrecht

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media Dordrecht 1994

  • Hardcover ISBN: 978-0-7923-2598-7Published: 31 December 1993

  • Softcover ISBN: 978-94-010-4344-1Published: 04 October 2012

  • eBook ISBN: 978-94-011-0800-3Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: XIII, 417

  • Topics: Probability Theory and Stochastic Processes, Statistical Theory and Methods

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