Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1153857 | Statistical Methodology | 2009 | 14 Pages |
Abstract
This paper concerns the estimation of a function at a point in nonparametric heteroscedastic regression models with Gaussian noise or noise having unknown distribution. In those cases an asymptotically efficient kernel estimator is constructed for the minimax absolute error risk.
Related Topics
Physical Sciences and Engineering
Mathematics
Statistics and Probability
Authors
J.-Y. Brua,