The Oxford handbook of functional data analysis / edited by F. Ferraty, Y. Romain.
"As technology progresses, we are able to handle larger and larger datasets. At the same time, monitoring devices such as electronic equipment and sensors (for registering images, temperature, etc.) have become more and more sophisticated. This high-tech revolution offers the opportunity to observe...
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| Language: | English |
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Oxford ; New York :
Oxford University Press, USA,
2011.
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| Physical Description: | pages ; cm. |
| Format: | Book |
Contents:
- Machine generated contents note:
- List of illustrations
- List of datasets
- PART I: REGRESSION MODELLING FOR FDA
- 1. Unifying presentation for functional regression modelling, F. Ferraty and P. Vieu
- 2. Functional linear regression, H. Cardot and P. Sarda
- 3. Linear processes for functional data, A. Mas and B. Pumo
- 4. Kernel regression estimation for functional data, F. Ferraty and P. Vieu
- 5. Nonparametric methods for alpha-mixing functional data, L. Delsol
- 6. Functional coefficient models for economics and financial data, Z. Cai
- PART II: BENCHMARK METHODS FOR FDA
- 7. Resampling methods for functional data, T. McMurry and D. Politis
- 8. Functional principal component analysis, P. Hall
- 9. Curve registration, J. Ramsay
- 10. Classification methods for functional data, A. Baillo, A. Cuevas, and R. Fraiman
- 11. Sparse functional data analysis, G. James
- PART III: TOWARDS STOCHASTIC BACKGROUND IN INFINITE-DIMENSIONAL SPACES
- 12. Vector integration in Banach spaces, N. Dinculeanu
- 13. Operator geometry in Statistics, K. Gustafson
- 14. On Bernstein type and maximal inequalities for dependent Banach-valued random vectors and applications, N. Rhomari
- 15. On spectral and random measures associated to a stationary process, A. Boudou and Y. Romain
- 16. An invitation to operator-based Statistics, Y. Romain
- Index.