Article ID Journal Published Year Pages File Type
1154027 Statistics & Probability Letters 2006 9 Pages PDF
Abstract
The paper deals with estimating problem of regression function at a given state point in nonparametric regression models with Gaussian noises and with non-Gaussian noises having unknown distribution. An asymptotically efficient kernel estimator is constructed for a minimax risk.
Keywords
Related Topics
Physical Sciences and Engineering Mathematics Statistics and Probability
Preview
Asymptotically efficient estimates for nonparametric regression models
Authors
, ,