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August 2006 Asymptotic equivalence of nonparametric autoregression and nonparametric regression
Ion G. Grama, Michael H. Neumann
Ann. Statist. 34(4): 1701-1732 (August 2006). DOI: 10.1214/009053606000000560

Abstract

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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Ion G. Grama. Michael H. Neumann. "Asymptotic equivalence of nonparametric autoregression and nonparametric regression." Ann. Statist. 34 (4) 1701 - 1732, August 2006. https://doi.org/10.1214/009053606000000560

Information

Published: August 2006
First available in Project Euclid: 3 November 2006

zbMATH: 1246.62105
MathSciNet: MR2283714
Digital Object Identifier: 10.1214/009053606000000560

Subjects:
Primary: 62B15
Secondary: 62G07 , 62G20

Keywords: ‎asymptotic ‎equivalence , deficiency distance , Gaussian approximation , Nonparametric autoregression , Nonparametric regression

Rights: Copyright © 2006 Institute of Mathematical Statistics

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Vol.34 • No. 4 • August 2006
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