Contents:

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

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