Multivariate Statistical Modeling and Data Analysis

1. Front Matter

   Pages i-ix

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2. On the Application of AIC to Bivariate Density Estimation, Nonparametric Regression and Discrimination

   • Taskin Atilgan, Tom Leonard

   Pages 1-16

3. On the Interface between Cluster Analysis, Principal Component Analysis, and Multidimensional Scaling

   • H. H. Bock

   Pages 17-34

4. An Expert Model Selection Approach to Determine the “Best” Pattern Structure in Factor Analysis Models

   • Hamparsum Bozdogan, Donald E. Ramirez

   Pages 35-60

5. Blus Residuals in Multivariate Linear Models

   • Vernon M. Chinchilli

   Pages 61-75

6. Analysis of Within- and Across-Subject Correlations

   • Sung C. Choi, Vernon M. Chinchilli

   Pages 77-93

7. Two-Stage Multi-Sample Cluster Analysis as a General Approach to Discriminant Analysis

   • Dorothea Eisenblätter, Hamparsum Bozdogan

   Pages 95-119

8. On Relationship Between the AIC and the Overall Error Rates for Selection of Variables in a Discriminant Analysis

   • Yasunori Fujikoshi

   Pages 121-138

9. Distribution of Likelihood Criteria and Box Approximation

   • A. K. Gupta, J. Tang

   Pages 139-145

10. Topics in the Analysis of Repeated Measurements

    • D. R. Jensen

    Pages 147-161

11. Metric Considerations in Clustering: Implications for Algorithms

    • Stanley L. Sclove

    Pages 163-186

12. Back Matter

    Pages 187-189

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This volume contains the Proceedings of the Advanced Symposium on Multivariate Modeling and Data Analysis held at the 64th Annual Heeting of the Virginia Academy of Sciences (VAS)--American Statistical Association's Vir­ ginia Chapter at James Madison University in Harrisonburg. Virginia during Hay 15-16. 1986. This symposium was sponsored by financial support from the Center for Advanced Studies at the University of Virginia to promote new and modern information-theoretic statist­ ical modeling procedures and to blend these new techniques within the classical theory. Multivariate statistical analysis has come a long way and currently it is in an evolutionary stage in the era of high-speed computation and computer technology. The Advanced Symposium was the first to address the new innovative approaches in multi­ variate analysis to develop modern analytical and yet practical procedures to meet the needs of researchers and the societal need of statistics. vii viii PREFACE Papers presented at the Symposium by e1l11lJinent researchers in the field were geared not Just for specialists in statistics, but an attempt has been made to achieve a well balanced and uniform coverage of different areas in multi­ variate modeling and data analysis. The areas covered included topics in the analysis of repeated measurements, cluster analysis, discriminant analysis, canonical cor­ relations, distribution theory and testing, bivariate densi ty estimation, factor analysis, principle component analysis, multidimensional scaling, multivariate linear models, nonparametric regression, etc.

• Clustering
• Factor analysis
• Likelihood
• cluster analysis
• correlation
• data analysis
• multidimensional scaling
• principal component analysis

• Department of Mathematics, University of Virginia, Charlottesville, USA

  H. Bozdogan

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

  A. K. Gupta

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