A new method for robust nonparametric regression
Consider the problem of estimating the mean function underlying a set of noisy data. Least squares is appropriate if the error distribution of the noise is Gaussian, and if there is good reason to believe that the underlying function has some particular form. But what if the previous two assumptions...
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Others |
| Language: | English |
| Published: |
2009
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/1911/16403 |