Asymptotic equivalence of nonparametric autoregression and nonparametric regression
Statistics Theory
2007-06-13 v1 Statistics Theory
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.
Keywords
Cite
@article{arxiv.math/0611257,
title = {Asymptotic equivalence of nonparametric autoregression and nonparametric regression},
author = {Ion G. Grama and Michael H. Neumann},
journal= {arXiv preprint arXiv:math/0611257},
year = {2007}
}
Comments
Published at http://dx.doi.org/10.1214/009053606000000560 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)