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

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页码：1701 / 1732

页数：32

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