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A User's Guide to Principal Components
Abstract
Preface.Introduction.1. Getting Started.2. PCA with More Than Two Variables.3. Scaling of Data.4. Inferential Procedures.5. Putting It All Together-Hearing Loss I.6. Operations with Group Data.7. Vector Interpretation I : Simplifications and Inferential Techniques.8. Vector Interpretation II: Rotation.9. A Case History-Hearing Loss II.10. Singular Value Decomposition: Multidimensional Scaling I.11. Distance Models: Multidimensional Scaling II.12. Linear Models I : Regression PCA of Predictor Variables.13. Linear Models II: Analysis of Variance PCA of Response Variables.14. Other Applications of PCA.15. Flatland: Special Procedures for Two Dimensions.16. Odds and Ends.17. What is Factor Analysis Anyhow?18. Other Competitors.Conclusion.Appendix A. Matrix Properties.Appendix B. Matrix Algebra Associated with Principal Component Analysis.Appendix C. Computational Methods.Appendix D. A Directory of Symbols and Definitions for PCA.Appendix E. Some Classic Examples.Appendix F. Data Sets Used in This Book.Appendix G. Tables.Bibliography.Author Index.Subject Index.
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Metadata
- Authors
- Leigh, S., & Jackson, J. E.
- Venue
- Technometrics
- Publisher
- JSTOR
- Published
- 1993-02
- Volume
- 35
- Issue
- 1
- Pages
- 84
- ISSN
- 0040-1706 (ISSN-L)
- OpenAlex
- W2152820192
- Cited by
- 3,332
- References
- 0
- FWCI
- 54.64
- Type
- journal article
- Language
- en
- Open access
- closed
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