Introduction to Nonparametric Regression

Acknowledgments.

1. Exordium.

2. Smoothing for Data with an Equispaced Predictor.

3. Nonparametric Regression for One-Dimensional Predictor.

4. Multidimensional Smoothing.

5. Nonparametric Regression with Predictors Represented as Distributions.

6. Smoothing of Histograms and Nonparametric Probability Density Functions.

7. Pattern Recognition.

Appendix A: Creation and Applications of B-Spline Bases.

Appendix B: R Objects.

Appendix C: Further Readings.

Index.