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.
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页码：1701 / 1732
页数：32
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