Includes bibliographical references (pages 293-302) and index.
CONTENTS NOTE
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1. Introduction -- 2. Notation and techniques -- 3. Representing functional data as smooth functions -- 4. The roughness penalty approach -- 5. The registration and display of functional data -- 6. Principal components analysis for functional data -- 7. Regularized principal components analysis -- 8. Principal components analysis of mixed data -- 9. Functional linear models -- 10. Functional linear models for scalar responses -- 11. Functional linear models for functional responses -- 12. Canonical correlation and discriminant analysis -- 13. Differential operators in functional data analysis -- 14. Principal differential analysis -- 15. More general roughness penalties -- 16. Some perspectives on FDA -- Appendix. Some algebraic and functional techniques.
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SUMMARY OR ABSTRACT
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Scientists today often collect samples of curves and other functional observations. This monograph presents many ideas and techniques for such data. Included are expressions in the functional domain of such classics as linear regression, principal components analysis, linear modeling, and canonical correlation analysis, as well as specifically functional techniques such as curve registration and principal differential analysis. Data arising in real applications are used throughout for both motivation and illustration, showing how functional approaches allow us to see new things, especially by exploiting the smoothness of the processes generating the data. The data sets exemplify the wide scope of functional data analysis, drawing from the fields of growth analysis, meteorology, biomechanics, equine science, economics, and medicine.
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The book presents novel statistical technology while keeping the mathematical level widely accessible. It is designed to appeal to students, applied data analysts, and experienced researchers, and will have value both within the statistics community and across a broad spectrum of other fields. Much of the material is based on the authors' own work, some of which appears here for the first time.