Asymptotic equivalence for nonparametric regression with multivariate and random design
统计理论
2007-06-13 v1 统计理论
摘要
We show that nonparametric regression is asymptotically equivalent in Le Cam's sense with a sequence of Gaussian white noise experiments as the number of observations tends to infinity. We propose a general constructive framework based on approximation spaces, which permits to achieve asymptotic equivalence even in the cases of multivariate and random design.
引用
@article{arxiv.math/0607342,
title = {Asymptotic equivalence for nonparametric regression with multivariate and random design},
author = {Markus Reiß},
journal= {arXiv preprint arXiv:math/0607342},
year = {2007}
}
备注
30 pages