| Topic： | Differential Equation-Assisted Local Polynomial Regression |
| Speaker： | Prof. W. John Braun (Professor and Head, Computer Science, Mathematics, Physics and Statistics Irving K. Barber School of Arts and Sciences University of British Columbia – Okanagan, CANADA) |
| Time： | 2015/5/1 (Fri.) AM 10:40 - 11:30 (Tea Time: AM 10:20 - 10:40, Room 821) |
| Place： | GENⅢ 837 |
| Abstract： | Use of higher-order local polynomial regression is often problematic in cases of data sparsity (which might be a result of data missing at random, for example). Although local constant regression is usable when data is sparse, the results can be misleading. If the underlying regression function is are assumed to satisfy or approximately satisfy a differential equation, a procedure with similar variance properties to local constant regression can be employed while achieving reasonable bias properties. |