| Date | Subject |
|---|---|
| 8-23 | Introduction; the empirical distribution function (R) |
| 8-28 | Statistical functionals and influence functions (R) |
| 8-30 | The functional delta method (R) |
| 9-4 | Connections between parametric and nonparametric theory |
| 9-6 | The jackknife |
| 9-11 | The bootstrap (R) |
| 9-13 | The geometry of the bootstrap (R) |
| 9-18 | Bootstrap confidence intervals (R) |
| 9-20 | Empirical likelihood (R) |
| 9-25 | Permutation tests |
| 9-27 | Rank tests (R) |
| 10-9 | Relative efficiency |
| 10-11 | Bootstrap tests (R) |
| 10-16 | Smoothing concepts (R) |
| 10-18 | Kernel density estimation (R) |
| 10-25 | Kernel density classification (R) |
| 10-30 | Introduction to nonparametric regression (R) (extra) |
| 11-1 | Local regression I (R) |
| 11-8 | Local regression II (R) |
| 11-13 | Local likelihood (R) |
| 11-20 | Splines (R) |
| 11-29 | Multiple regression and additive models (R) |
| 12-4 | Tree-based methods (R) |
Some miscellaneous R functions: fun.R