Book contents
- Frontmatter
- PART I Regression smoothing
- PART II The kernel method
- 4 How close is the smooth to the true curve?
- 5 Choosing the smoothing parameter
- 6 Data sets with outliers
- 7 Nonparametric regression techniques for correlated data
- 8 Looking for special features and qualitative smoothing
- 9 Incorporating parametric components
- PART III Smoothing in high dimensions
- Appendix 1
- Appendix 2
- References
- Name Index
- Subject Index
7 - Nonparametric regression techniques for correlated data
from PART II - The kernel method
Published online by Cambridge University Press: 05 January 2013
Book contents
- Frontmatter
- PART I Regression smoothing
- PART II The kernel method
- 4 How close is the smooth to the true curve?
- 5 Choosing the smoothing parameter
- 6 Data sets with outliers
- 7 Nonparametric regression techniques for correlated data
- 8 Looking for special features and qualitative smoothing
- 9 Incorporating parametric components
- PART III Smoothing in high dimensions
- Appendix 1
- Appendix 2
- References
- Name Index
- Subject Index
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- Applied Nonparametric Regression , pp. 203 - 216Publisher: Cambridge University PressPrint publication year: 1990