Asymptotic equivalence for nonparametric regression with multivariate and random design

Details Asymptotic equivalence for nonparametric regression with multivariate and random design Asymptotic equivalence for nonparametric regression with multivariate and random design

2006-07-14

arxiv.org/abs/math/0607342v1

Mathematics

Statistics Theory

30 pages

Scientific paper

We show that nonparametric regression is asymptotically equivalent in Le
Cam's sense with a sequence of Gaussian white noise experiments as the number
of observations tends to infinity. We propose a general constructive framework
based on approximation spaces, which permits to achieve asymptotic equivalence
even in the cases of multivariate and random design.

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