Nonparametric Functional Data Analysis Theory and Practice
Rather than set application against theory, this book is really an interface of these two features of statistics. A special effort has been made in writing this book to accommodate several levels of reading. The computational aspects are oriented toward practitioners whereas open problems emerging f...
| Main Authors: | , |
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| Format: | eBook |
| Language: | English |
| Published: |
New York, NY
Springer New York
2006, 2006
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| Edition: | 1st ed. 2006 |
| Series: | Springer Series in Statistics
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| Subjects: | |
| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- Statistical Background for Nonparametric Statistics and Functional Data
- to Functional Nonparametric Statistics
- Some Functional Datasets and Associated Statistical Problematics
- What is a Well-Adapted Space for Functional Data?
- Local Weighting of Functional Variables
- Nonparametric Prediction from Functional Data
- Functional Nonparametric Prediction Methodologies
- Some Selected Asymptotics
- Computational Issues
- Nonparametric Classification of Functional Data
- Functional Nonparametric Supervised Classification
- Functional Nonparametric Unsupervised Classification
- Nonparametric Methods for Dependent Functional Data
- Mixing, Nonparametric and Functional Statistics
- Some Selected Asymptotics
- Application to Continuous Time Processes Prediction
- Conclusions
- Small Ball Probabilities and Semi-metrics
- Some Perspectives