Asymptotic equivalence of nonparametric autoregression and nonparametric regression

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.

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)

References in corpus (2)

• Asymptotic Equivalence for Nonparametric Regression
• Statistical properties of the method of regularization with periodic Gaussian reproducing kernel

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