Asymptotic equivalence of nonparametric autoregression and nonparametric regression

被引：10
|
作者：
Grama, Ion G.
Neumann, Michael H.
机构：
[1] Univ Bretagne Sud, Ctr Rech Yves Coppens, F-56000 Vannes, France
[2] Univ Jena, Inst Stochast, D-07743 Jena, Germany
来源：
ANNALS OF STATISTICS | 2006年 / 34卷 / 04期
关键词：
asymptotic equivalence; deficiency distance; Gaussian approximation; nonparametric autoregression; nonparametric regression;
D O I：
10.1214/009053606000000560
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
It is proved that nonparametric autoregression is asymptotically equivalent in the sense of Le Cam's deficiency distance to nonparametric regression with random design as well as with regular nonrandom design.
引用
收藏
页码：1701 / 1732
页数：32
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